Stryker

Senior Engineer, EDT Data & Analytics - Data Engineering

Gurugram, HR

Actively hiring, first seen by us 1 day ago

Pay: Pay not listed
Work setting: Not stated
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 and optimize scalable ETL/ELT pipelines, data models, and data marts
Develop automated data workflows using orchestration tools
Build efficient SQL and Python/Scala-based transformation processes
Ensure data quality, governance, and security with validation and monitoring
Support cloud data platforms and deliver business-driven data solutions

From the employer’s posting

Design and optimize scalable ETL/ELT pipelines, data models, and data marts

Develop automated data workflows using orchestration tools

building efficient SQL and Python/Scala-based transformation processes

Ensure data quality, governance, security, and compliance through robust validation, monitoring, and error-handling frameworks

Support cloud data platforms and collaborate with stakeholders to deliver high-performance, business-driven data solutions

What you’ll bring

All qualifications

Core experience

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline required with 3-5 years of experience in data engineering, ETL development, or database development.
Strong proficiency in SQL and hands-on experience with at least one programming language (Python, Scala, or Java).
Ability to analyze complex data requirements and translate them into scalable technical solutions.
Experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse along with hands on experience in building and maintaining data pipelines on-premises or in a cloud environment.
Experience with workflow orchestration tools such as Apache Airflow, Azure Data Factory, or dbt.
Familiarity with CI/CD practices and version control (Git) for data engineering workflows and understanding of data modeling techniques (dimensional modeling, star schema, data vault)., knowledge of Data Lake, Lakehouse and Unity Catalogue Concepts, use of Tool’s AI features to bring efficiency in Coding and bug fixing

Qualification wording

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline required with 3-5 years of experience in data engineering, ETL development, or database development.

Strong proficiency in SQL and hands-on experience with at least one programming language (Python, Scala, or Java).

Ability to analyze complex data requirements and translate them into scalable technical solutions.

Experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse along with hands on experience in building and maintaining data pipelines on-premises or in a cloud environment.

Experience with workflow orchestration tools such as Apache Airflow, Azure Data Factory, or dbt. And streaming technologies such as Kafka, Kinesis, or Event Hubs.

Familiarity with CI/CD practices and version control (Git) for data engineering workflows and understanding of data modeling techniques (dimensional modeling, star schema, data vault)., knowledge of Data Lake, Lakehouse and Unity Catalogue Concepts, use of Tool’s AI features to bring efficiency in Coding and bug fixing

Education & alternatives

Required Skills: - Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline required with 3-5 years of experience in data engineering, ETL development, or database development. - Strong proficiency in SQL and hands-on experience with at least one programming language (Python, Scala, or Java).

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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: 2
Last seen by us: Nov 3, 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

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 5 and day 54.

From 10,736 similar postings that came down. Coming down is not always a hire.

Stryker is hiring

25 open jobs

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

Data Engineer hiring is picking up
Takes jobs down at a usual pace

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.

Java
Python
Scala
SQL
AWS
Azure
Databricks
dbt
GCP
Kafka
Redshift
Snowflake
Airflow

Where the posting names them

- Support cloud data platforms and collaborate with stakeholders to deliver high-performance, business-driven data solutions. - Strong expertise in data engineering, including batch/streaming processing, SQL, and programming with Python, Scala, or Java. - Hands-on experience with distributed data frameworks, cloud data platforms, and modern data warehouse/lakehouse technologies.

- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline required with 3-5 years of experience in data engineering, ETL development, or database development. - Strong proficiency in SQL and hands-on experience with at least one programming language (Python, Scala, or Java). - Working knowledge of relational databases and data warehousing/lakehouse concepts.

- Design and optimize scalable ETL/ELT pipelines, data models, and data marts to enable reliable analytics and reporting. - Develop automated data workflows using orchestration tools while building efficient SQL and Python/Scala-based transformation processes. - Ensure data quality, governance, security, and compliance through robust validation, monitoring, and error-handling frameworks.

- Ability to analyze complex data requirements and translate them into scalable technical solutions. - Experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse along with hands on experience in building and maintaining data pipelines on-premises or in a cloud environment. - Experience with workflow orchestration tools such as Apache Airflow, Azure Data Factory, or dbt. And streaming technologies such as Kafka, Kinesis, or Event Hubs.

- Familiarity with CI/CD practices and version control (Git) for data engineering workflows and understanding of data modeling techniques (dimensional modeling, star schema, data vault)., knowledge of Data Lake, Lakehouse and Unity Catalogue Concepts, use of Tool’s AI features to bring efficiency in Coding and bug fixing - Cloud platform certification (AWS, Azure, or GCP Data Engineer track) preferred./ Snowflake, Databricks, or equivalent data platform certification preferred

- Experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse along with hands on experience in building and maintaining data pipelines on-premises or in a cloud environment. - Experience with workflow orchestration tools such as Apache Airflow, Azure Data Factory, or dbt. And streaming technologies such as Kafka, Kinesis, or Event Hubs. - Familiarity with CI/CD practices and version control (Git) for data engineering workflows and understanding of data modeling techniques (dimensional modeling, star schema, data vault)., knowledge of Data Lake, Lakehouse and Unity Catalogue Concepts, use of Tool’s AI features to bring efficiency in Coding and bug fixing

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

The Data Engineer designs, builds, and maintains scalable data pipelines and integration solutions that power analytics, reporting, and business decision-making. This role works closely with Data Architects, Analysts, and Platform teams to ingest, transform, and deliver reliable, high-quality data across the Data and Analytics ecosystem, while following established engineering standards and best practices.

What you will do:

Design and optimize scalable ETL/ELT pipelines, data models, and data marts to enable reliable analytics and reporting.
Develop automated data workflows using orchestration tools while building efficient SQL and Python/Scala-based transformation processes.
Ensure data quality, governance, security, and compliance through robust validation, monitoring, and error-handling frameworks.
Support cloud data platforms and collaborate with stakeholders to deliver high-performance, business-driven data solutions.
Strong expertise in data engineering, including batch/streaming processing, SQL, and programming with Python, Scala, or Java.
Hands-on experience with distributed data frameworks, cloud data platforms, and modern data warehouse/lakehouse technologies.
Proven ability to troubleshoot complex technical issues, ensure data quality, and deliver reliable, scalable data solutions.
Collaborative and adaptable professional who works effectively across teams, embraces new technologies, and independently drives results.

What you will need:

Required Skills:

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline required with 3-5 years of experience in data engineering, ETL development, or database development.
Strong proficiency in SQL and hands-on experience with at least one programming language (Python, Scala, or Java).
Working knowledge of relational databases and data warehousing/lakehouse concepts.
Ability to analyze complex data requirements and translate them into scalable technical solutions.
Experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse along with hands on experience in building and maintaining data pipelines on-premises or in a cloud environment.
Experience with workflow orchestration tools such as Apache Airflow, Azure Data Factory, or dbt. And streaming technologies such as Kafka, Kinesis, or Event Hubs.
Familiarity with CI/CD practices and version control (Git) for data engineering workflows and understanding of data modeling techniques (dimensional modeling, star schema, data vault)., knowledge of Data Lake, Lakehouse and Unity Catalogue Concepts, use of Tool’s AI features to bring efficiency in Coding and bug fixing
Cloud platform certification (AWS, Azure, or GCP Data Engineer track) preferred./ Snowflake, Databricks, or equivalent data platform certification preferred

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