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Senior (8+ yrs) Databricks specialization at a mid-tier consultancy reduces applicant competition.
Deep Databricks/Spark, Delta Lake, and data platform expertise limits transferability across non-data roles.
Explicit 8+ years plus mandatory Databricks, Python, SQL and cloud expertise enforces strict filtering.
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Lead design, development, and implementation of scalable data pipelines using Databricks, Spark, and related technologies.
Provide technical leadership and mentorship to a team of data engineers ensuring high-performance, maintainable data solutions.
Architect and optimize enterprise data platform components including Databricks Lakehouse, Delta Lake, Unity Catalog, and Spark workloads.
8+ years of data engineering experience with 2-3 years in a lead or senior role.
Extensive hands-on experience with Databricks platform including Spark on Databricks, Delta Lake, Delta Live Tables (DLT), Photon, and SQL Analytics.
Strong programming skills in Python (PySpark) and SQL.
Bachelor's or Master's degree in Computer Science, Engineering, or related quantitative field.
Experienced in architecting and optimizing large-scale data platforms on Databricks in enterprise settings, preferably in transportation or similar domains.
Skilled in leading and mentoring teams with a focus on applying best practices, coding standards, and maintaining high code quality.
Proficient in cloud data services (AWS/Azure/GCP) and familiar with CI/CD workflows and orchestration tools like Apache Airflow or Databricks Workflows.