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Senior (10+ years) Databricks/Spark specialization and smaller employer reduce applicant density.
Specialized Databricks and Big Data skills moderately limit transferability across industries.
Explicit 10+ years requirement plus mandatory Databricks, Spark, Delta Lake and Big Data skills.
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Own architecture and design of data engineering solutions using Databricks on cloud platforms (Azure, AWS, GCP).
Manage large-scale Big Data platform implementations including Hadoop ecosystem and Delta Lake for Lakehouse architecture.
Lead development and maintenance of data pipelines, data warehouse solutions, and ensure CI/CD and DevOps integration for data workflows.
10+ years of experience in data engineering with strong Python and PySpark skills.
3–5+ years hands-on experience with Databricks platform on Azure, AWS, or GCP.
Deep understanding of Apache Spark internals, distributed computing, and Big Data technologies (Hadoop, Hive, HDFS).
Proficiency in SQL and experience with relational/non-relational databases; familiar with CI/CD, Git, DevOps tools, and data orchestration tools (e.g., Airflow, Azure Data Factory).
Experienced in designing and maintaining data warehouses and lakehouse architectures using Delta Lake.
Skilled in agile development processes, collaborating effectively in cross-functional teams with strong communication skills.
Capable of managing SDLC stages, producing status reports, and working proactively in dynamic environments.