Top Data Engineer Jobs

As a Data Engineer II at Stackline, you will build scalable data systems, develop ETL processes, and collaborate with cross-functional teams to optimize data workflows.

Build and automate zero-config ingestion pipelines for major marketing and CRM platforms, transform third-party JSON into analytical schemas, map event data into unified identity/event streams, and integrate Martech data into the core ClickHouse/ML environment.

Lead design and delivery of large data products and pipelines, mentor senior engineers, set standards and best practices, promote data/analytics across business units, collaborate on governance and curated data catalog, and present technical work externally.

Architect and scale cloud data platforms and ETL/ELT pipelines (batch and near-real-time), ensure data quality and observability, implement CI/CD for data infrastructure, collaborate with stakeholders and mentor junior engineers to deliver analytics and machine-learning-ready data products.

Develop, maintain, and run data ingestion and analytics pipelines (Python, Lambda, Pig, PySpark). Review data ingest tickets and merge requests, ensure accurate data delivery and day-to-day operations, investigate data arrival issues, and support system authorization, RMF compliance, and vulnerability management.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Design, build, and own robust batch and real-time data pipelines and golden datasets using SQL and Python. Ensure data quality, performance, schema design, and SLAs while partnering across engineering, product, and business teams. Advocate tooling and best practices, document datasets, and deliver reliable analytics infrastructure at petabyte scale.

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.

Lead ownership of data infrastructure and ETL: design, build, and maintain Airflow pipelines ingesting from Postgres and SaaS sources; optimize Snowflake/BigQuery warehouses and dbt transformations; drive architecture, mentor teammates, and align data platform roadmap with business needs.

Lead design and implementation of scalable batch and streaming data infrastructure. Build and maintain ETL/ELT pipelines, ensure data quality and observability, troubleshoot production issues, mentor engineers, and partner with cross-functional teams to deliver reliable, self-serve data products.

Design, develop, and maintain large-scale data architectures and pipelines; deploy cloud-native data applications and CI/CD; support ML model productization; enforce code hygiene and best practices; mentor junior engineers; produce documentation and runbooks; collaborate with consulting teams and clients and travel as required.

Lead design and implementation of data lake architecture and cloud data platforms. Develop and optimize ETL/Delta Lake pipelines, administer Databricks, integrate AI/ML workflows, enforce cloud security/RBAC, and collaborate with analysts, developers, and clients to deliver compliant solutions.

Lead design and implementation of scalable data architectures and pipelines (real-time and batch), mentor junior engineers, ensure pipeline reliability and security, adopt new tools, collaborate cross-functionally, and implement data governance.

Design, build, and execute data pipelines and migration strategies to move legacy data into Temenos systems. Perform data mapping, cleansing, testing, validation, and post-migration support. Collaborate with stakeholders, QA, and vendors, use Temenos migration and ETL tools, and document transformation logic while ensuring data integrity and minimal cutover downtime.

Lead design, build, and optimize scalable ETL/ELT pipelines and enterprise semantic layers on Snowflake. Develop semantic models, implement data quality, performance tune queries, automate maintenance, enable analytics self-service, and enforce governance while mentoring engineers and collaborating with cross-functional stakeholders.

The Senior Data Engineer will design and maintain data architectures, work with operations teams, solve complex data challenges, and document decisions for stakeholders.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

Lead design and implementation of scalable ETL/ELT pipelines and Snowflake data models. Optimize workflows, ensure data quality and observability, support BI (Tableau, Domo, Power BI), mentor engineers, and drive data platform architecture and roadmap.

10-week summer internship working on large-scale data pipelines and operational data delivery. Interns join either the Person Data team (Java-focused analytics and data quality) or the Data Engineering team (build LLM + vector-database chatbots for proactive data quality). Emphasis on debugging, reliability, and learning with experienced mentors.

Designs, builds, and maintains cloud-based ETL/ELT data pipelines and platforms on AWS/Azure (Airflow, Snowflake). Develops CI/CD pipelines, performs DevOps, database development, data architecture, testing, and supports multiple project phases to deliver reliable, reusable data solutions.

The Data Engineer will build and maintain scalable data pipelines, optimize data for AI/ML models, and collaborate with engineers to ensure data quality and integration across systems.

As a Data Engineer, you will develop and manage the data infrastructure that supports HTS Media's advertising business, build ETL/ELT pipelines, and enable data-driven insights for advertisers and internal analytics.

The role involves developing scalable data pipelines, automating workflows, optimizing data models, and ensuring data governance while collaborating with various teams.

As a Data Engineer, you will create efficient data models, pipelines, and analytics frameworks, collaborating with various departments to transform raw data into actionable insights.

Looking for a Data Engineer focused on data visualization with experience in handling real-world data and effective communication through data. Extra credit for skills in probabilistic classifiers and full-text search engines.