Senior Data Engineer
New
R
RearcData engineering
Remote (USA)Full-TimeSenior
Salary155,000 - 190,000 USD per year
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Job Details
- Experience
- 6+ years of hands-on data engineering experience
- Required Skills
- AWSPythonGCPAzureSparkScalaDatabricks
Requirements
- Have 6+ years of hands-on data engineering experience designing and delivering production-grade data platforms.
- Bring expert-level 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.
- Apply DataOps practices including CI/CD for data pipelines, automated testing, observability, and infrastructure as code.
- Have experience in ETL/ELT design, data warehousing, lakehouse architecture, and data modeling.
- Communicate effectively with technical and non-technical stakeholders.
Responsibilities
- Contribute to architecture and technical delivery on client data engagements.
- Design and implement scalable 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.
- Support technical scope and timelines, identify blockers, and coordinate with project managers and client stakeholders.
- Mentor junior and mid-level engineers through pairing, code review, and feedback.
- Contribute technical blogs, reference architectures, and internal guides.
- Establish data engineering standards for testing, observability, version control, CI/CD, and documentation.
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