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Strong Tier-1 brand plus mid-level data engineer manager and common Databricks/Python skills create medium competition.
Explicit financial services/consulting experience requirement creates high background fit sensitivity across industries.
Mandatory 7+ years, Databricks/Spark/Python and financial services experience make shortlisting requirements high.
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Design, develop, test, and maintain scalable data pipelines and applications primarily using Python, PySpark, SQL, and Databricks.
Build and manage Databricks workflows, containerized applications (Docker), and CI/CD pipelines with tools like Jenkins and Artifactory.
Collaborate with cross-functional teams to define requirements, lead projects end-to-end, and serve as a technical and domain Subject Matter Expert.
Minimum 7 years of experience in technology/data functions within financial services or consulting industry.
Hands-on experience with Databricks ecosystem, Python-based application development and deployment, and cloud platforms (preferably AWS).
Strong skills in Python, PySpark, SQL, shell scripting, data modeling, ETL frameworks, and CI/CD tools (Jenkins, Artifactory, Bitbucket).
Bachelor's degree or equivalent related work experience.
Experienced in fast-paced, dynamically growing sectors with proven ability to establish data strategies and implement data transformations.
Capable of leading projects independently with strong ownership of deliverables and cross-team collaboration.
Deep understanding of distributed data processing, Spark architecture, and cloud-based data application deployment and troubleshooting.