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Senior Data Engineer Jobs (On-site work)

124 Job Offers

Senior Data Engineer
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Seeking a Senior Data Engineer in Hyderabad to design and optimize complex data pipelines using Databricks, PySpark, and AWS. You will build scalable ETL frameworks and enable enterprise data governance. Requires 9-12 years' expertise in big data, distributed computing, and Agile/SAFe methodologies.
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India , Hyderabad
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Not provided
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Amgen
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Until further notice
Senior Data Engineer
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Seeking a Senior Data Engineer in Hyderabad to design and optimize scalable data pipelines on AWS and Databricks. You will leverage Python/Scala and ETL orchestration within a SAFE Agile team to ensure data integrity and performance. This role requires 6+ years' experience, mastery of modern data...
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India , Hyderabad
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Amgen
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Until further notice
Senior Data Integration Engineer
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Join Crusoe Cloud as a Senior Data Integration Engineer. Design scalable ETL/ELT pipelines using Fivetran, Workato, and DBT on GCP. Enable critical data flow for analytics and AI infrastructure from our Sunnyvale or San Francisco offices. Enjoy competitive pay, equity, and comprehensive benefits.
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United States , Sunnyvale; San Francisco
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147000.00 - 178000.00 USD / Year
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Crusoe
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Until further notice
Senior Data Engineer
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Join a global Energy Trading firm in London as a Senior Data Engineer. Build greenfield data pipelines on AWS using Python and SQL to power trading decisions. Leverage your ETL expertise and market data knowledge (EPEX, ENTSO-E) in this high-impact role.
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United Kingdom , London
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Orbis Consultants
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Until further notice

About the Senior Data Engineer role

Discover and apply for Senior Data Engineer jobs, a critical role at the intersection of data architecture, software engineering, and analytics. Senior Data Engineers are the master builders of the data world, responsible for designing, constructing, and maintaining the robust infrastructure that transforms raw, often chaotic data into a reliable, accessible, and high-quality resource for an entire organization. These professionals move beyond basic data processing to architect scalable platforms that serve as the single source of truth, enabling data-driven decision-making, advanced analytics, and machine learning.

In this senior capacity, individuals typically take ownership of the entire data pipeline lifecycle. Common responsibilities include architecting and implementing both batch and real-time streaming data pipelines on major cloud platforms like AWS, GCP, or Azure. They design and enforce canonical data models, schemas, and data contracts to ensure consistency and integrity. A key part of the role is building and maintaining curated data marts, lakes, or warehouses that power business intelligence tools, dashboards, and APIs for downstream consumers such as data analysts, scientists, and product teams. Furthermore, Senior Data Engineers champion data governance, implementing rigorous data quality checks, observability, monitoring, and security protocols like access controls and PII handling to build trusted data products.

The technical skill set for these jobs is extensive and deep. Proficiency in SQL is fundamental, alongside expert-level programming in Python, Scala, or Java for building data processing logic. Hands-on experience with a modern tech stack is essential, including tools like Apache Spark, Kafka, and orchestration frameworks such as Apache Airflow. They are expected to be adept with cloud-native data services (e.g., BigQuery, Redshift, Snowflake, Databricks, Dataflow) and practices like Infrastructure-as-Code (IaC) and CI/CD for data systems. Beyond technical prowess, successful Senior Data Engineers possess strong problem-solving skills to turn ambiguous business needs into elegant technical solutions. They exhibit leadership by mentoring junior engineers, defining best practices, automating workflows, and collaborating effectively with cross-functional teams to align data architecture with strategic business goals. If you are seeking Senior Data Engineer jobs, you are looking for a role that demands a blend of deep technical expertise, strategic architectural thinking, and a commitment to building the foundational systems that unlock an organization's data potential.