Data Engineer

Morgan Stanley seeks a Data Engineer - Parametric in Mumbai, India, to join our dynamic team. This role involves full lifecycle development, from requirements gathering and design to implementation, testing, deployment, and support. You will design and implement robust, scalable data solutions that align with project timelines and business objectives.

Key responsibilities include developing, testing, and maintaining data pipelines and applications for enterprise data platforms. You will write and optimize complex SQL queries for ETL processes, and create and maintain essential documentation such as ER diagrams, data flow diagrams, and architectural designs. Ensuring consistency and integration of data solutions across teams and systems is crucial.

This position offers the opportunity to expand data platform capabilities to meet new business challenges and data needs. You will implement data security, backup, and recovery strategies in accordance with organizational policies. Collaboration with business stakeholders and project managers is expected for designing logical and physical data models, resolving data model conflicts, and ensuring alignment with enterprise data standards.

You will contribute to the development and enforcement of data management policies, procedures, and standards. Evaluating emerging technologies and providing recommendations for adoption or improvement, as well as supporting business continuity and disaster recovery planning for data systems, are also key aspects of this role.

Required Skills: SQL, Python, PySpark, Bash, AWS CLI, Snowflake CLI, AWS, Databricks, DBT, Data Warehousing, Data Lake, Data Lakehouse, Kafka, Apache Iceberg, Great Expectations, Databricks Unity Catalog, Tableau, Power BI.

Qualifications: A Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent professional experience. Minimum of 5 years of hands-on experience in data engineering, data science, or software development. At least 3 years of experience with Snowflake, including data modeling and performance tuning. 4+ years of experience with AWS or similar cloud platforms (S3, IAM, Athena, RDS, DMS, Glue, KMS, SNS, SQS, EMR). Proficiency in Python and Linux/Unix shell scripting. Strong background in designing and architecting scalable, distributed data systems using open-source technologies.

Preferred Skills: Familiarity with modern data architecture paradigms like data lakes, data lake houses, and data mesh, with practical implementation experience. Proven experience in Agile or other iterative development environments. Solid understanding of object-oriented programming principles, design patterns, and software engineering best practices. Deep expertise in data modeling and various data structures. Experience with Big Data tools for batch and real-time processing. Excellent collaboration and communication skills, with the ability to translate technical concepts for diverse audiences. Demonstrated ability to foster accountability, teamwork, and continuous improvement. A Master's degree in Computer Science, Mathematics, or Engineering is a plus. AWS/Snowflake certifications are advantageous. Experience with reporting tools like Power BI or Tableau. Financial industry experience is a plus.