Python Developer - Senior Associate

Job Description

Job Purpose

As a key member of the DTS team, you will primarily collaborate closely with a leading global hedge fund on data engagements. Partner

with data strategy and sourcing team on data requirements to design data pipelines and delivery structures.

• Engage with vendors and technical teams to systematically ingest, evaluate, and create valuable data assets.
• Collaborate with core engineering team to create central capabilities to process, manage and distribute data assts at scale.
• Interpret business requirements and work with internal resources as well as application vendors.
• Design, develop, and maintain custom data engineering pipelines.
• Troubleshoot and resolve data-related issues.
• Configure and create data models and data quality rules to meet customer needs.
• Review and analyze data from multiple internal and external sources.
• Analyze existing Python code and identify areas for optimization.
• Write new optimized SQL queries or Python scripts to improve performance and reduce run time.
• Identify opportunities for efficiency and innovative approaches to completing the scope of work.
• Write clean, efficient, and well-documented code that adheres to best practices and Council IT coding standards.
• Deliver results under demanding timelines to real-world business problems.
• Work independently and multi-task effectively.
• Configure system settings and options and execute unit/integration testing.
• Apply robust data quality rules to systemically qualify data deliveries and guarantee the integrity of financial datasets.
• Engage with technical and non-technical clients as SME on data asset offerings.
• Good communication (verbal and written)
• Experience in managing client stakeholders

Key competencies

• B.Tech/ M.Tech/ MCA with 4+ years of overall experience.
• Skilled in Python and SQL.
• Experience with data modeling, data warehousing, and building data pipelines.
• Experience working with FTP, API, S3 and other distribution channels to source data.
• Experience working with financial and/or alternative data products.
• Experience working with cloud native tools for data processing and distribution.
• Experience with Snowflake, Airflow, Databricks, and PySpark

• AI/ML, LLM