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Senior Data Engineer
Noida, India
Actively hiring, first seen by us 1 day ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign and optimize scalable pipelines with Databricks, Spark, PySpark and Delta Lake
Build medallion (Bronze, Silver, Gold) architecture for analytics-ready datasets
Build and maintain integrations with enterprise apps, REST APIs and databases
Build batch and near-real-time ingestion with incremental loads and CDC
Implement Unity Catalog governance, access controls and sensitive-data protection
From the employer’s posting
Design, develop, and optimize scalable data pipelines using Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake.
Design and implement a medallion architecture (Bronze, Silver, and Gold layers)
Build and maintain integrations with enterprise applications, REST APIs, databases, and other source systems
Build reliable batch and near-real-time ingestion pipelines with incremental loads, CDC, schema evolution and error recovery.
Implement Unity Catalog governance, including access controls, lineage, auditing, and sensitive-data protection through masking and row-level security.
What you’ll bring
All qualificationsCore experience
- 5+ years of experience in data engineering or a related technical role, including developing and supporting production data pipelines.
- Experience with Databricks Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables), Auto Loader, and advanced incremental ingestion patterns.
- Strong proficiency in Python/PySpark, SQL, and Apache Spark for scalable data processing and transformation.
- Experience implementing Unity Catalog governance, including fine-grained access controls, data lineage, auditing, and sensitive-data protection.
- Practical experience with Delta Lake, including table management, incremental processing, and performance optimization.
- Experience with Databricks Genie, Genie Agents, and Genie Code
Qualification wording
5+ years of experience in data engineering or a related technical role, including developing and supporting production data pipelines.
Experience with Databricks Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables), Auto Loader, and advanced incremental ingestion patterns.
Strong proficiency in Python/PySpark, SQL, and Apache Spark for scalable data processing and transformation.
Experience implementing Unity Catalog governance, including fine-grained access controls, data lineage, auditing, and sensitive-data protection.
Practical experience with Delta Lake, including table management, incremental processing, and performance optimization.
Experience with Databricks Genie, Genie Agents, and Genie Code
Posting record
Report an errorActively 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 13, 20261 day ago
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Sumo Logic is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee 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
- SQL
- AWS
- Databricks
- Delta Lake
- Redshift
- S3
- Spark
- PySpark
Where the posting names them
We are looking for a highly skilled Senior Data Engineer to design, build, and maintain scalable data pipelines and integrations within our Databricks-based data platform. The role will focus on expanding our data ecosystem by onboarding new data sources, integrating enterprise applications, and delivering reliable, secure, and analytics-ready datasets. The ideal candidate will have strong hands-on expertise in Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake, along with experience building production-grade data pipelines and enterprise integrations. Working knowledge of AWS infrastructure and cloud services is important for collaborating with Engineering and other platform teams on connectivity, deployments, and evolving infrastructure requirements. The candidate will report directly to the Senior Manager - Business Insights & Analytics and collaborate with Data Analytics, Engineering, IT/Cloud, Security, and business stakeholders to deliver scalable and reliable data solutions.
Responsibilities: - Design, develop, and optimize scalable data pipelines using Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake. - Design and implement a medallion architecture (Bronze, Silver, and Gold layers) to deliver trusted, well-structured, analytics-ready datasets.
- Strong hands-on expertise in Databricks, including developing, troubleshooting, and optimizing production workloads. - Strong proficiency in Python/PySpark, SQL, and Apache Spark for scalable data processing and transformation. - Practical experience with Delta Lake, including table management, incremental processing, and performance optimization.
- Configure and manage Databricks Workflows and implement ingestion and transformation pipelines using Auto Loader and Lakeflow Spark Declarative Pipelines - Optimize Apache Spark and Delta Lake workloads using execution-plan analysis, efficient join strategies, data-skew handling, partitioning, and SQL query tuning to improve performance and control compute costs. - Implement Unity Catalog governance, including access controls, lineage, auditing, and sensitive-data protection through masking and row-level security.
- Understanding of reliable data processing patterns, including retries, idempotency, schema evolution, backfills, and failure recovery. - Working knowledge of AWS services and cloud infrastructure, particularly IAM roles and policies, S3 storage and access management, and secure connectivity between source systems and data platforms. - Experience with Git/GitHub, code reviews, automated testing, and CI/CD practices.
Sr Data Engineer-Noida(Hybrid) We are looking for a highly skilled Senior Data Engineer to design, build, and maintain scalable data pipelines and integrations within our Databricks-based data platform. The role will focus on expanding our data ecosystem by onboarding new data sources, integrating enterprise applications, and delivering reliable, secure, and analytics-ready datasets. The ideal candidate will have strong hands-on expertise in Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake, along with experience building production-grade data pipelines and enterprise integrations. Working knowledge of AWS infrastructure and cloud services is important for collaborating with Engineering and other platform teams on connectivity, deployments, and evolving infrastructure requirements.
- Build reliable batch and near-real-time ingestion pipelines with incremental loads, CDC, schema evolution and error recovery. - Configure and manage Databricks Workflows and implement ingestion and transformation pipelines using Auto Loader and Lakeflow Spark Declarative Pipelines - Optimize Apache Spark and Delta Lake workloads using execution-plan analysis, efficient join strategies, data-skew handling, partitioning, and SQL query tuning to improve performance and control compute costs.
- 5+ years of experience in data engineering or a related technical role, including developing and supporting production data pipelines. - Strong hands-on expertise in Databricks, including developing, troubleshooting, and optimizing production workloads. - Strong proficiency in Python/PySpark, SQL, and Apache Spark for scalable data processing and transformation.
- Experience with data architecture and modeling, including medallion architecture and the development of analytics-ready datasets. - Experience with Databricks Workflows or equivalent orchestration solutions. - Proven experience building data ingestion pipelines and integrating REST APIs, databases, and enterprise applications.
Desirable: - Experience with Databricks Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables), Auto Loader, and advanced incremental ingestion patterns. - Experience implementing Unity Catalog governance, including fine-grained access controls, data lineage, auditing, and sensitive-data protection.
- Experience implementing Unity Catalog governance, including fine-grained access controls, data lineage, auditing, and sensitive-data protection. - Experience with Databricks Genie, Genie Agents, and Genie Code - Experience in AI/ML, Data Science, LLMs, contextualization, Amazon Bedrock
- Strong proficiency in Python/PySpark, SQL, and Apache Spark for scalable data processing and transformation. - Practical experience with Delta Lake, including table management, incremental processing, and performance optimization. - Experience with data architecture and modeling, including medallion architecture and the development of analytics-ready datasets.
- Implement Unity Catalog governance, including access controls, lineage, auditing, and sensitive-data protection through masking and row-level security. - Maintain and support existing data workflows running on Amazon Redshift and Amazon EC2, collaborating with Engineering and IT/Cloud teams on connectivity, IAM permissions, S3 access, deployments, and operational issues. - Follow engineering best practices, including version control, code reviews, automated testing, CI/CD, and technical documentation.
Your next step
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About Sumo Logic
- People
- About 479 in 2024.Benefit plan filings (Form 5500)
- Company
- Listed as SUMO.
- H-1B visas
- 6 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
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
Sr Data Engineer-Noida(Hybrid)
We are looking for a highly skilled Senior Data Engineer to design, build, and maintain scalable data pipelines and integrations within our Databricks-based data platform. The role will focus on expanding our data ecosystem by onboarding new data sources, integrating enterprise applications, and delivering reliable, secure, and analytics-ready datasets.
The ideal candidate will have strong hands-on expertise in Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake, along with experience building production-grade data pipelines and enterprise integrations. Working knowledge of AWS infrastructure and cloud services is important for collaborating with Engineering and other platform teams on connectivity, deployments, and evolving infrastructure requirements.
The candidate will report directly to the Senior Manager - Business Insights & Analytics and collaborate with Data Analytics, Engineering, IT/Cloud, Security, and business stakeholders to deliver scalable and reliable data solutions.
Responsibilities:
- Design, develop, and optimize scalable data pipelines using Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake.
- Design and implement a medallion architecture (Bronze, Silver, and Gold layers) to deliver trusted, well-structured, analytics-ready datasets.
- Build and maintain integrations with enterprise applications, REST APIs, databases, and other source systems
- Developing reusable ingestion frameworks to accelerate onboarding of new data sources.
- Build reliable batch and near-real-time ingestion pipelines with incremental loads, CDC, schema evolution and error recovery.
- Configure and manage Databricks Workflows and implement ingestion and transformation pipelines using Auto Loader and Lakeflow Spark Declarative Pipelines
- Optimize Apache Spark and Delta Lake workloads using execution-plan analysis, efficient join strategies, data-skew handling, partitioning, and SQL query tuning to improve performance and control compute costs.
- Implement Unity Catalog governance, including access controls, lineage, auditing, and sensitive-data protection through masking and row-level security.
- Maintain and support existing data workflows running on Amazon Redshift and Amazon EC2, collaborating with Engineering and IT/Cloud teams on connectivity, IAM permissions, S3 access, deployments, and operational issues.
- Follow engineering best practices, including version control, code reviews, automated testing, CI/CD, and technical documentation.
- Partner with Data Analytics and business stakeholders to translate requirements into trusted, well-documented, analytics-ready datasets.
- Provide technical guidance to team members and identify opportunities to improve automation, engineering standards, platform reliability, and resource utilization.
Requirements:
- 5+ years of experience in data engineering or a related technical role, including developing and supporting production data pipelines.
- Strong hands-on expertise in Databricks, including developing, troubleshooting, and optimizing production workloads.
- Strong proficiency in Python/PySpark, SQL, and Apache Spark for scalable data processing and transformation.
- Practical experience with Delta Lake, including table management, incremental processing, and performance optimization.
- Experience with data architecture and modeling, including medallion architecture and the development of analytics-ready datasets.
- Experience with Databricks Workflows or equivalent orchestration solutions.
- Proven experience building data ingestion pipelines and integrating REST APIs, databases, and enterprise applications.
- Understanding of reliable data processing patterns, including retries, idempotency, schema evolution, backfills, and failure recovery.
- Working knowledge of AWS services and cloud infrastructure, particularly IAM roles and policies, S3 storage and access management, and secure connectivity between source systems and data platforms.
- Experience with Git/GitHub, code reviews, automated testing, and CI/CD practices.
- Strong problem-solving skills and the ability to independently design, build, deploy, and maintain production data solutions.
- Good communication and collaboration skills to work effectively with Data Analytics, Engineering, IT/Cloud, Security, and business stakeholders.
Desirable:
- Experience with Databricks Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables), Auto Loader, and advanced incremental ingestion patterns.
- Experience implementing Unity Catalog governance, including fine-grained access controls, data lineage, auditing, and sensitive-data protection.
- Experience with Databricks Genie, Genie Agents, and Genie Code
- Experience in AI/ML, Data Science, LLMs, contextualization, Amazon Bedrock
Sumo Logic, Inc. helps make the digital world secure, fast, and reliable by unifying critical security and operational data through its Intelligent Operations Platform. Built to address the increasing complexity of modern cybersecurity and cloud operations challenges, we empower digital teams to move from reaction to readiness—combining agentic AI-powered SIEM and log analytics into a single platform to detect, investigate, and resolve modern challenges. Customers around the world rely on Sumo Logic for trusted insights to protect against security threats, ensure reliability, and gain powerful insights into their digital environments. For more information, visit www.sumologic.com.
Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection.
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Noida, India
Sr Data Engineer-Noida(Hybrid) We are looking for a highly skilled Senior Data Engineer to design, build, and maintain scalable data pipelines and integrations within our Databricks-based data platform. The role will focus on expanding our data ecosystem by onboarding new data sources, integrating enterprise applications, and delivering reliable, secure, and analytics-ready datasets.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.