Data Engineer - Parametric at Morgan Stanley

Mumbai, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

26 Feb, 26

Salary

0.0

Posted On

28 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, PySpark, Bash, AWS, Snowflake, Databricks, DBT, Data Warehousing, Data Lake, Data Lakehouse, Kafka, Apache Iceberg, Great Expectations, Tableau, Power BI

Industry

Financial Services

Description

Collaborate on development projects across the full lifecycle: requirements gathering, design, implementation, testing, deployment, and support. Design and implement robust, scalable data solutions aligned with project timelines and business objectives. Develop, test, and maintain data pipelines and applications to support enterprise data platforms. Write and optimize complex SQL queries for data extraction, transformation, and loading (ETL). Create and maintain documentation including ER diagrams, data flow diagrams, and architectural designs. Ensure consistency and integration of data solutions across teams and systems. Expand data platform capabilities to address new business challenges and data needs. Implement data security, backup, and recovery strategies in line with organizational policies. Design logical and physical data models in collaboration with business stakeholders and project managers. Resolve data model conflicts and ensure alignment with enterprise data standards. Contribute to the development and enforcement of data management policies, procedures, and standards. Evaluate emerging technologies and provide recommendations for adoption or improvement. Support business continuity and disaster recovery planning for data systems. Skill set: 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 Bachelor's degree in computer science, Engineering, Mathematics, or a related field—or equivalent professional experience. 5+ years of hands-on experience in data engineering, data science, or software development roles. Minimum 3 years of experience working with Snowflake, including data modeling and performance tuning. 4+ years of experience with AWS or similar cloud platforms, including services like S3, IAM, Athena, RDS, DMS, Glue, KMS, SNS, SQS, and EMR. Proficient in programming with Python and scripting in Linux/Unix shell environments. Strong background in designing and architecting scalable, distributed data systems using opensource technologies. Familiarity with modern data architecture paradigms such as data lakes, data lake houses, and data mesh, with practical exposure to their implementation and strategic use. Proven experience working 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, with a strong grasp of various data structures and their optimal use cases. Experience with Big Data tools for both batch and real time data processing. Excellent collaboration skills with the ability to work effectively across cross functional teams. Strong communication skills, capable of translating technical concepts for business stakeholders and nontechnical audiences. Demonstrated ability to foster a culture of accountability, teamwork, and continuous improvement. Master's degree in computer science, Mathematics, Engineering or similar is a plus Certifications in AWS/Snowflake Experience with reporting tools like Power BI, Tableau or similar Financial Industry experience a plus Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.

Responsibilities

Collaborate on development projects across the full lifecycle, including requirements gathering, design, implementation, testing, deployment, and support. Design and implement robust, scalable data solutions aligned with project timelines and business objectives.