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Tier-1 bank, metro location, and popular data engineering title create high candidate competition.
Core data engineering skills transfer across industries, though financial domain knowledge increases specificity.
Explicit 6+ years plus mandatory data, Snowflake, Azure, Spark, and Kafka skills enforce strict filters.
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Own end-to-end delivery of business functionality for Settlement users within an Agile team, including developing new reports and data provisioning solutions.
Collaborate directly with business users and regulators to understand and fulfill data requirements.
Leverage strong Python, SQL, and cloud platform skills to build and maintain critical data engineering solutions aligned with post-trade operations.
Minimum 6+ years of relevant experience in data engineering or related field.
Strong programming skills in Python, including data manipulation libraries such as Pandas, NumPy, Dask.
Proficiency in SQL and experience with relational databases and Snowflake.
Experience with cloud platforms (preferably Azure), data warehousing, ETL/ELT processes, Apache Spark, Apache Airflow, and version control (Git).
Experienced data engineer skilled in end-to-end Agile delivery within financial services, particularly post-trade settlements or related operational functions.
Hands-on expertise in Python programming for data manipulation and analytics, with strong familiarity with SQL and modern cloud data technologies.
Effective collaborator able to engage directly with business users and regulators to translate complex requirements into data solutions.