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Tier-1 brand plus metro and generalist data role raise applicant density, balanced by seniority and specialized skillset.
Core data engineering technologies (SQL, Python, Databricks, Airflow) are broadly transferable across industries.
Explicit 9+ years plus mandatory Databricks, Python, Airflow, SQL, cloud and DataOps make filters stringent.
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Design, build, and maintain scalable data pipelines and analytical data models supporting cross-functional business needs.
Integrate and prepare data from structured and unstructured enterprise sources including Databricks and IT data platforms.
Ensure data quality, observability, and document technical information clearly for non-technical stakeholders.
Bachelor's or Master's degree in Computer Science, Data Engineering, or related technical field.
9+ years of experience in data engineering or related domains.
Proficiency in SQL, advanced Python, ETL/ELT, and orchestration tools (e.g., Airflow, Dagster, Prefect).
Onsite work primarily from an HPE office (Location requirement).
Experienced with cloud storage/distributed systems (AWS S3, Hadoop, Hive, Snowflake) and cloud platforms (AWS, GCP, Azure).
Demonstrates strong ownership from design through delivery and can translate technical concepts to business partners clearly.
Able to work independently and prioritize multiple projects in a fast-paced environment, balancing technical depth with business understanding.