Top Senior Data Engineer Jobs

In this role, you will design data architecture, lead integration strategies, mentor engineers, and drive AI infrastructure for cross-division data systems.

As a Senior Data Engineer, you'll build ETL pipelines, design data ingestion systems, and maintain a multi-cloud ecosystem while collaborating with Data Scientists to transform data into business insights.

The Senior Data Engineer will optimize the data platform, build scalable data pipelines, improve data access and quality, and establish data engineering discipline within the company.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

Design, build, and maintain large-scale data structures and ETL pipelines using Hadoop/Hive, SQL, Python/Java. Support real-time and offline analytics, create data marts/models, integrate data sources, ensure data quality, collaborate with Data Science, and produce reporting/BI outputs.

Design, build, and optimize scalable data pipelines and architectures using SQL and AWS big-data technologies. Assemble complex datasets, automate processes, enable analytics and stream processing, secure cross-region data, and support cross-functional stakeholders including data scientists and product teams.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Lead and grow the data engineering team to evolve a cloud-native data platform: design pipelines, improve ETL/ELT and orchestration, ensure data quality and governance, enable BI and data products, manage infrastructure budget, and enforce security and operational best practices while partnering with product and business teams.

Senior Data Engineer responsible for designing and implementing data solutions, ensuring data quality, and optimizing data systems.

Lead ETL and data architecture for AML, trade/sales surveillance, and compliance data repositories. Design and develop complex Informatica PowerCenter 9.1 mappings, enforce ETL architecture standards, tune performance, automate and maintain ETL utilities, collaborate with BAs and DBAs, provide production support, and mentor junior ETL developers.

Design and implement large-scale data processing solutions (GB/PB) using Hadoop, NoSQL, MPP and related open-source tech. Participate in architecture/design, provide implementation details to offshore teams, produce whitepapers/case studies, ensure timely quality deliveries, and share knowledge through training sessions.

Design, implement, and maintain enterprise database solutions and Big Data (Hadoop) systems. Lead database architecture, HA/DR, migrations, patching, performance tuning, security, capacity planning, monitoring, and incident recovery. Provide technical leadership, SOP documentation, and support BI/data mining activities. Role requires shift work.

Design and build scalable platforms for data ingestion and storage, collaborate with hardware engineers, and define engineering processes at Sift.

As a Senior Data Engineer, you'll transform raw data into datasets, design production pipelines, integrate customer data, and collaborate with various teams to ensure data quality and reliability.

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

Lead design and delivery of large-scale data pipelines and warehouse systems. Define technical strategy, enforce data governance, improve developer efficiency, mentor engineers, and align data engineering efforts with business goals to enable analytics and ML at scale.

Design, build, and maintain data warehouses, data marts, and OLAP solutions; develop ETL frameworks, data models, SSIS/SSAS/SSRS artifacts, and performance-tuned SQL Server databases to support analytics and visualization projects.

Design, develop, maintain and test scalable big data solutions. Build preprocessing and reporting pipelines, collect/parse/analyze/visualize large datasets, test and deploy machine-learning models on big data, and work in agile teams to deliver analytics solutions.

Design, develop, test and maintain scalable big-data solutions and workflows. Collect, parse, analyze and visualize large datasets; evaluate, test and deploy machine-learning models for scoring and prediction. Work in an agile team, automate tasks using scripting, and leverage Hadoop/Spark and AWS for production pipelines.

The Senior Data Engineer designs and maintains data pipelines and architectures to support enterprise analytics, ensuring data quality and integration across systems.

Design, build and deliver SAP-originated and non‑SAP data in formats consumable by non‑SAP tools and external B2B partners using SAP BO/Data Services, BW/BI. Support ETL, integration and data delivery processes.

Design and build IBM DataStage ETL jobs to extract, transform, and load data into 3NF and star schemas. Implement Slowly Changing Dimensions and Change Data Capture, write strong Oracle SQL, use QualityStage and parallel processing, create source-to-target mappings, write/execute test cases, and use Unix shell scripting. Collaborate with stakeholders and maintain data warehouse ETL processes.

Lead design and build of a cloud-based big data analytics platform: implement analytics infrastructure, integrate streaming and batch data, develop distributed processing pipelines, manage predictive analytics models, and apply machine learning and Bayesian methods. Work involves Scala on OS X and AWS, Java and Clojure, Kafka/Samza, NoSQL, and following TDD, Agile, CI/CD practices.

Lead design and scaling of enterprise data architecture and pipelines. Build and maintain ETL/ELT and CDC/streaming workflows, improve data quality and observability, own schema and warehouse modeling, implement governance (RBAC), and provide cross-functional technical leadership to enable trusted, scalable data for analytics and product teams.

Lead design, build, and optimization of the enterprise data warehouse and production data pipelines. Own platform architecture, integrate legacy systems (AS400), support Power BI semantic models (DAX), implement monitoring, CI/CD and governance, and mentor engineers to transition from consultant-run platforms to an internally managed, scalable data ecosystem.