Design, build, and optimize scalable ETL/ELT pipelines using Databricks and Apache Spark. Develop high-performance data solutions on cloud platforms, primarily Azure. Collaborate with IT and business stakeholders to deliver curated and analytics-ready datasets.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Duration: 12+ months
Location: 100% remote (EST hours)
Responsibilities
- Design, build, and optimize scalable ETL/ELT pipelines using Databricks and Apache Spark.
- Develop high-performance data solutions on cloud platforms, primarily Azure.
- Ensure data quality, reliability, scalability, and performance across data workflows.
- Collaborate with IT and business stakeholders to deliver curated and analytics-ready datasets.
- Automate and orchestrate workflows using Databricks Jobs, CI/CD pipelines, and related tools.
- Implement best practices around data governance, monitoring, and platform security.
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Qualifications
- Strong hands-on experience with Databricks, Apache Spark (PySpark and/or Scala), SQL, and Kafka.
- Experience building data solutions in cloud environments such as Azure, AWS, or GCP.
- Knowledge of Delta Lake, CDC, distributed data processing, and data modeling concepts.
- Familiarity with Git, CI/CD pipelines, and workflow orchestration tools.
- Solid understanding of data architecture, performance tuning, and optimization techniques.
- Retail industry experience is a plus.
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