Lead Data Engineer

🔥 11 hours ago

🇺🇸 United States – Remote

💵 $180k - $220k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

Where this job comes from

Posted on Rearc's careers page, not through a job board

First seen by Remote Rocketship 11 hours ago

Still open on Rearc's site. Checked 2 hours ago.

Logo of Rearc

Rearc

51 - 200 employees

🤖 Artificial Intelligence

Artificial Intelligence • Cloud

Rearc is a boutique, engineering-driven services firm specializing in cloud, data, and generative AI solutions. They are known for their innovation and engineering delivery excellence, empowering small teams to achieve significant results and foster creativity. Rearc offers services such as GenAI quickstart, secure data collaboration, data platform foundation, and cloud platform engineering. Their services are comprehensive and adaptable to meet the specific needs of their clients. Rearc has expertise in building foundational data platform capabilities, cloud governance, and the use of AWS products.

📋 Description

• Serve as the senior technical lead on client projects • Own solution architecture, guide the build, manage delivery risk, and ensure delivered solutions match commitments • Design and implement scalable, reliable data pipelines and lakehouse architectures on Databricks and cloud platforms • Write and review production-quality code and set engineering standards • Translate complex client requirements into technical designs, reference architectures, and data models • Manage technical scope and timelines and identify blockers early • Partner with project managers and client stakeholders to keep engagements on track • Coach junior and mid-level engineers through pairing, code review, and direct feedback • Contribute technical blogs, reference architectures, and internal guides • Establish and enforce DataOps standards including automated testing, pipeline observability, version control, CI/CD, and documentation

🎯 Requirements

• 8+ years of hands-on data engineering experience, designing and delivering production-grade data platforms • Expert-level in Apache Spark, including runtime internals, performance tuning, and optimization • Clean, production-quality code in Python • Experience with Scala is a strong plus • Experience building and productionizing solutions on Databricks, including Delta Lake architectures, Unity Catalog governance, and Databricks Workflows • Databricks certification is a strong plus • Experience across at least two major cloud platforms (AWS, Azure, GCP), with genuine depth in at least one • Experience with cloud-native services such as AWS Redshift/Glue/S3, Azure Synapse/Data Factory/ADLS, or Google BigQuery/Dataflow/GCS • Track record leading data engineering projects end-to-end in a client-facing or consulting context • Experience managing technical scope, stakeholder expectations, and delivery timelines • CI/CD for data pipelines, automated testing, observability, and infrastructure-as-code experience • Experience spanning ETL/ELT design, data warehousing, lakehouse architecture, and data modeling • Strong communication skills with technical and non-technical stakeholders

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