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Senior Data and Analytics Engineer

North Chicago, IL, United States

Actively hiring, first seen by us 1 day ago
Pay
Pay not listedSimilar roles state $122K–$190K
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Design, build, and support production-grade batch and streaming data pipelines

  • Implement lakehouse and warehouse solutions on S3, Iceberg, Glue, EMR, and Redshift

  • Define data product contracts, ownership, quality expectations, and lineage

  • Build ingestion and orchestration with Airflow, dbt, or Step Functions

  • Embed data-quality, security, and governance controls in pipelines

From the employer’s posting
Design, develop, test, deploy, and support production-grade data pipelines and data products
Implement solutions using Amazon S3, Apache Iceberg/open table formats, AWS Glue Data Catalog, Amazon EMR/Spark, Amazon Redshift and Redshift Spectrum
Define product contracts, ownership, metadata, quality expectations, service-level objectives, lineage
Develop orchestration using tools such as Apache Airflow, dbt, AWS Step Functions or equivalent approved platforms
Embed automated data-quality controls, reconciliation, schema validation, lineage, cataloging, retention, encryption, least-privilege access, and auditability

What you’ll bring

All qualifications

Core experience

  • Bachelor’s Degree in Computer Science, Information Systems, Data Engineering, or a related field plus 7 years of relevant experience; Master's Degree plus 6 years of experience; PhD plus 2 years of experience.
  • Experience with streaming technologies such as Amazon Kinesis, Apache Kafka, Spark Structured Streaming, or equivalent platforms.
  • Demonstrated experience building large Lakehouse and modern warehouse solutions using Amazon S3, Apache Iceberg or comparable open table formats, AWS Glue, Amazon EMR, Amazon Redshift, and Redshift Spectrum.
  • Experience exposing data through APIs, semantic models, governed data services, or feature/context layers for AI-enabled applications.
  • Proven experience with medallion architecture, data modeling, schema design, incremental processing, change data capture, partitioning, performance tuning, and cost optimization.
  • 5+ years of hands-on experience designing and delivering enterprise modern data warehouse, Lakehouse, data engineering, and analytical solutions.
Qualification wording
Bachelor’s Degree in Computer Science, Information Systems, Data Engineering, or a related field plus 7 years of relevant experience; Master's Degree plus 6 years of experience; PhD plus 2 years of experience.
Experience with streaming technologies such as Amazon Kinesis, Apache Kafka, Spark Structured Streaming, or equivalent platforms.
Demonstrated experience building large Lakehouse and modern warehouse solutions using Amazon S3, Apache Iceberg or comparable open table formats, AWS Glue, Amazon EMR, Amazon Redshift, and Redshift Spectrum.
Experience exposing data through APIs, semantic models, governed data services, or feature/context layers for AI-enabled applications.
Proven experience with medallion architecture, data modeling, schema design, incremental processing, change data capture, partitioning, performance tuning, and cost optimization.
5+ years of hands-on experience designing and delivering enterprise modern data warehouse, Lakehouse, data engineering, and analytical solutions.
Education & alternatives
Required: - Bachelor’s Degree in Computer Science, Information Systems, Data Engineering, or a related field plus 7 years of relevant experience; Master's Degree plus 6 years of experience; PhD plus 2 years of experience. - Respective years of hands-on experience designing and delivering enterprise modern data warehouse, Lakehouse, data engineering, and analytical solutions.

About AbbVie

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow.

In the employer’s words · Read in context

Apply at AbbVie

Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20261 day ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$122K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 321 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 6 and day 47.

From 1,405 similar postings that came down. Coming down is not always a hire.

AbbVie is hiring

86 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 27% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Scala
  • SQL
  • AWS
  • dbt
  • Iceberg
  • Kafka
  • Redshift
  • S3
  • Spark
  • Airflow
  • PySpark
Where the posting names them
- Respective years of hands-on experience designing and delivering enterprise modern data warehouse, Lakehouse, data engineering, and analytical solutions. - Advanced proficiency in SQL and Python, with strong hands-on experience in PySpark or Scala and distributed data processing on Apache Spark/EMR or a comparable platform. - Demonstrated experience building large Lakehouse and modern warehouse solutions using Amazon S3, Apache Iceberg or comparable open table formats, AWS Glue, Amazon EMR, Amazon Redshift, and Redshift Spectrum.
- Hands-on engineering and solution delivery: Design, develop, test, deploy, and support production-grade data pipelines and data products for structured, semi-structured, and unstructured data. Build for both batch and near-real-time/streaming patterns, with reusable components, parameterized frameworks, and automated recovery. - Lakehouse and modern data warehouse architecture: Implement solutions using Amazon S3, Apache Iceberg/open table formats, AWS Glue Data Catalog, Amazon EMR/Spark, Amazon Redshift and Redshift Spectrum. Apply medallion patterns (Bronze, Silver, Gold), dimensional and domain-oriented modeling, workload isolation, partitioning, clustering/sort strategies, and performance optimization. - Data product and data mesh enablement: Translate business domains into discoverable, interoperable, and governed data products. Define product contracts, ownership, metadata, quality expectations, service-level objectives, lineage, and approved consumption patterns for dashboards, self-service analytics, APIs, data science, and AI.
- Data product and data mesh enablement: Translate business domains into discoverable, interoperable, and governed data products. Define product contracts, ownership, metadata, quality expectations, service-level objectives, lineage, and approved consumption patterns for dashboards, self-service analytics, APIs, data science, and AI. - Ingestion and orchestration: Engineer reliable ingestion from enterprise applications, databases, files, APIs, and event streams. Develop orchestration using tools such as Apache Airflow, dbt, AWS Step Functions or equivalent approved platforms, with dependency management, idempotency, observability, alerting, and backfill capability. - Data quality, governance, and security: Embed automated data-quality controls, reconciliation, schema validation, lineage, cataloging, retention, encryption, least-privilege access, and auditability. Partner with data governance, security, privacy, architecture, and platform teams to meet AbbVie standards and regulated-industry expectations.
- Advanced proficiency in SQL and Python, with strong hands-on experience in PySpark or Scala and distributed data processing on Apache Spark/EMR or a comparable platform. - Demonstrated experience building large Lakehouse and modern warehouse solutions using Amazon S3, Apache Iceberg or comparable open table formats, AWS Glue, Amazon EMR, Amazon Redshift, and Redshift Spectrum. - Proven experience with medallion architecture, data modeling, schema design, incremental processing, change data capture, partitioning, performance tuning, and cost optimization.
- Experience developing production-grade batch and streaming data pipelines, including orchestration, retries, backfills, observability, alerting, and operational support. - Hands-on experience with data transformation and orchestration tools such as Apache Airflow, AWS Step Functions or approved equivalents. - Experience implementing CI/CD, automated testing, Git-based development, infrastructure-as-code, and Agile DevOps delivery practices.
- Strong analytical, problem-solving, communication, and stakeholder-management skills, with the ability to work effectively across technical and business teams in a matrixed organization. - Experience with data catalogs, lineage, and governance platforms such as Alation, AWS Glue Data Catalog, or approved equivalents. Preferred:
- Experience with streaming technologies such as Amazon Kinesis, Apache Kafka, Spark Structured Streaming, or equivalent platforms. - Working experience with AWS Lake Formation, IAM, Secrets Manager, CloudWatch, CloudTrail, and enterprise controls for secure data platforms. - Experience exposing data through APIs, semantic models, governed data services, or feature/context layers for AI-enabled applications.
- Supply Chain or Operations domain knowledge across planning, sourcing, inventory, manufacturing, logistics, or distribution. - Experience with streaming technologies such as Amazon Kinesis, Apache Kafka, Spark Structured Streaming, or equivalent platforms. - Working experience with AWS Lake Formation, IAM, Secrets Manager, CloudWatch, CloudTrail, and enterprise controls for secure data platforms.

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Job description

View original posting ↗

Job Description

The Senior Data and Analytics Engineer will be responsible for translating complex business and data requirements into scalable, secure, and high-performing analytics and data engineering solutions for the Operations (Supply Chain) organization. The role will partner closely with internal DATA (Data, AI, Transformation and Automation) teams, and cross functional Business Technology Solutions (BTS), business stakeholders, architects, and delivery teams to understand strategic priorities and design, build, and deliver modern data solutions that enables analytics, business intelligence, and AI use cases. 

This role requires a strong combination of hands-on technical expertise and strategic thinking, understanding the North Star platform architecture to implement practical engineering solutions while ensuring alignment with enterprise architecture, development standards, data governance, security, and engineering best practices.

The individual will also provide technical leadership throughout the solution lifecycle, proactively manage technical risks and dependencies, and communicate effectively with both technical and business stakeholders. 

Responsibilities 

  • Hands-on engineering and solution delivery: Design, develop, test, deploy, and support production-grade data pipelines and data products for structured, semi-structured, and unstructured data. Build for both batch and near-real-time/streaming patterns, with reusable components, parameterized frameworks, and automated recovery. 
  • Lakehouse and modern data warehouse architecture: Implement solutions using Amazon S3, Apache Iceberg/open table formats, AWS Glue Data Catalog, Amazon EMR/Spark, Amazon Redshift and Redshift Spectrum. Apply medallion patterns (Bronze, Silver, Gold), dimensional and domain-oriented modeling, workload isolation, partitioning, clustering/sort strategies, and performance optimization. 
  • Data product and data mesh enablement: Translate business domains into discoverable, interoperable, and governed data products. Define product contracts, ownership, metadata, quality expectations, service-level objectives, lineage, and approved consumption patterns for dashboards, self-service analytics, APIs, data science, and AI. 
  • Ingestion and orchestration: Engineer reliable ingestion from enterprise applications, databases, files, APIs, and event streams. Develop orchestration using tools such as Apache Airflow, dbt, AWS Step Functions or equivalent approved platforms, with dependency management, idempotency, observability, alerting, and backfill capability. 
  • Data quality, governance, and security: Embed automated data-quality controls, reconciliation, schema validation, lineage, cataloging, retention, encryption, least-privilege access, and auditability. Partner with data governance, security, privacy, architecture, and platform teams to meet AbbVie standards and regulated-industry expectations. 
  • DevSecOps and engineering excellence: Establish source-control, code-review, automated testing, CI/CD, infrastructure-as-code, environment promotion, release management, and operational monitoring practices. Improve reliability, cost, performance, and developer productivity through measurable engineering standards. 
  • Business partnership and technical leadership: Understands organization's vision, goals, and strategies and partner with DATA, BTS, Operations stakeholders to translate complex requirements into scalable designs. Provide technical direction, resolve design and delivery issues, communicate risks and trade-offs, and contribute to portfolio prioritization and roadmap decisions. 
  • Operational ownership: Own solutions through the full lifecycle, including production readiness, deployment, support transition, incident resolution, root-cause analysis, technical debt reduction, and continuous improvement. Work with minimal oversight while escalating material risks early. 

 

Qualifications

Required:

  • Bachelor’s Degree in Computer Science, Information Systems, Data Engineering, or a related field plus 7 years of relevant experience; Master's Degree plus 6 years of experience; PhD plus 2 years of experience. 
  • Respective years of hands-on experience designing and delivering enterprise modern data warehouse, Lakehouse, data engineering, and analytical solutions. 
  • Advanced proficiency in SQL and Python, with strong hands-on experience in PySpark or Scala and distributed data processing on Apache Spark/EMR or a comparable platform. 
  • Demonstrated experience building large Lakehouse and modern warehouse solutions using Amazon S3, Apache Iceberg or comparable open table formats, AWS Glue, Amazon EMR, Amazon Redshift, and Redshift Spectrum. 
  • Proven experience with medallion architecture, data modeling, schema design, incremental processing, change data capture, partitioning, performance tuning, and cost optimization. 
  • Experience developing production-grade batch and streaming data pipelines, including orchestration, retries, backfills, observability, alerting, and operational support. 
  • Hands-on experience with data transformation and orchestration tools such as Apache Airflow, AWS Step Functions or approved equivalents. 
  • Experience implementing CI/CD, automated testing, Git-based development, infrastructure-as-code, and Agile DevOps delivery practices. 
  • Demonstrated ability to build governed, AI-ready data products that support BI, self-service analytics, data science, machine learning, and contextual AI consumption. 
  • Strong analytical, problem-solving, communication, and stakeholder-management skills, with the ability to work effectively across technical and business teams in a matrixed organization. 
  • Experience with data catalogs, lineage, and governance platforms such as Alation, AWS Glue Data Catalog, or approved equivalents. 

Preferred: 

  • Supply Chain or Operations domain knowledge across planning, sourcing, inventory, manufacturing, logistics, or distribution. 
  • Experience with streaming technologies such as Amazon Kinesis, Apache Kafka, Spark Structured Streaming, or equivalent platforms. 
  • Working experience with AWS Lake Formation, IAM, Secrets Manager, CloudWatch, CloudTrail, and enterprise controls for secure data platforms. 
  • Experience exposing data through APIs, semantic models, governed data services, or feature/context layers for AI-enabled applications. 
  • Relevant cloud or data engineering certifications are beneficial but not required. 
  • 5+ years of hands-on experience designing and delivering enterprise modern data warehouse, Lakehouse, data engineering, and analytical solutions. 

 

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​

  • The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. ​

  • We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.​

  • This job is eligible to participate in our long-term incentive programs. ​

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.​

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.  Equal Opportunity Employer/Veterans/Disabled. 

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html

Company Description

About AbbVie

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

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North Chicago, IL, United States

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