Senior Data Engineer

Rearc

1d • $155,000 - $190,000

About The Position

As a Senior Data Engineer at Rearc, you will serve as a technical anchor on complex, client-facing data engineering engagements. You will work with client data leadership to understand challenging data problems and build effective solutions, using hands-on expertise with Databricks and the modern data stack. You will help establish technical standards and design, build, and deliver production-ready data platforms alongside your team and clients.

The role combines technical contribution, solution architecture, implementation, and delivery support. You will build and productionize pipelines and lakehouse architectures, translate requirements into robust designs, help keep engagements on track, mentor engineers, share technical knowledge, and promote modern DataOps practices across projects.

Requirements

• At least 6 years of hands-on data engineering experience designing and delivering production-grade data platforms.
• Expert-level Apache Spark knowledge, including runtime internals, performance tuning, and optimization.
• Ability to write clean, production-quality Python code.
• Experience building and productionizing solutions on Databricks, including Delta Lake architectures, Unity Catalog governance, and Databricks Workflows.
• Working experience across at least two major cloud platforms (AWS, Azure, or GCP), with genuine depth in at least one.
• Experience with cloud-native services, such as AWS Redshift, Glue, or S3; Azure Synapse, Data Factory, or ADLS; or Google BigQuery, Dataflow, or GCS.
• A DataOps mindset and experience with CI/CD for data pipelines, automated testing, observability, and infrastructure as code.
• Experience with ETL/ELT design, data warehousing, lakehouse architecture, and data modeling, and the judgment to select appropriate approaches.
• Strong communication skills for engaging both technical and non-technical stakeholders.

Nice To Haves

• Scala experience, particularly for deeper Spark work and performance-critical applications.
• Databricks certification.

Responsibilities

• Serve as a senior technical contributor on client projects, contributing to architecture, guiding implementation, and helping ensure delivered solutions meet commitments.
• Design and implement scalable, reliable data pipelines and lakehouse architectures on Databricks and cloud platforms; write and review code and set engineering standards.
• Translate complex client requirements into robust technical designs, reference architectures, and production-ready data models.
• Support technical scope and timelines, identify blockers early, and work with project managers and client stakeholders to keep engagements on track.
• Mentor junior and mid-level data engineers through pairing, code reviews, and direct feedback.
• Contribute technical blogs, reference architectures, and internal guides based on lessons from client work.
• Establish and enforce data engineering standards, including automated testing, pipeline observability, version control, CI/CD, and documentation.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed