Lead Data Engineer
New
R
RearcData engineering
Remote (USA)Full-TimeLead
Salary180,000 - 220,000 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 8+ years of hands-on data engineering experience
- Required Skills
- AWSPythonAzureSparkDatabricks
Requirements
- Have 8+ years of hands-on data engineering experience designing and delivering production-grade data platforms.
- Bring expert Apache Spark knowledge, including runtime internals, performance tuning, and optimization.
- Write clean, production-quality Python code.
- Have experience building and productionizing solutions on Databricks, including Delta Lake architectures, Unity Catalog governance, and Databricks Workflows.
- Have working experience across at least two major cloud platforms (AWS, Azure, or GCP), with depth in at least one.
- Have experience with cloud-native services such as AWS Redshift, Glue, or S3; Azure Synapse, Data Factory, or ADLS; or Google BigQuery, Dataflow, or GCS.
- Have led data engineering projects end-to-end in a client-facing or consulting context, managing technical scope, stakeholder expectations, and timelines.
- Apply DataOps practices including CI/CD for data pipelines, automated testing, observability, and infrastructure as code.
- Have experience with ETL/ELT design, data warehousing, lakehouse architecture, and data modeling.
- Scala experience is a strong plus; Databricks certification is also a strong plus.
Responsibilities
- Lead client data engagements and own architecture, implementation, delivery risk, and solution quality.
- Design and build scalable, reliable data pipelines and lakehouse architectures on Databricks and cloud platforms.
- Write and review code and set engineering standards for client engagements.
- Translate client requirements into technical designs, reference architectures, and production data models.
- Manage technical scope and timelines, identify blockers, and work with project managers and client stakeholders to keep engagements on track.
- Mentor junior and mid-level data engineers through pairing, code review, and feedback.
- Contribute technical blogs, reference architectures, and internal guides.
- Establish data engineering standards for automated testing, observability, version control, CI/CD, and documentation.
View Full Description & ApplyYou'll be redirected to the employer's site
