Snowflake/Python Data Engineer

Senior Data Engineer / Data Analyst (Financial Data, Index & Analytics)

Location: Pune / Mumbai / Bangalore / Chennai

Experience: 5+ Years

Positions Available: 2

About Company: At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’ s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honoured with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 13,950+ and has 52 offices in 20 countries within key global markets. For more information on the company, please visit our website or LinkedIn community.

Diversity, Equity, and Inclusion Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and an affirmative-action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

Key Responsibilities:

• Design, develop, and optimize databases using advanced SQL techniques including CTEs, Window Functions, Dynamic SQL, and complex Joins.
• Implement effective indexing strategies (Clustered, Non-Clustered, Columnstore) and perform execution plan tuning to enhance performance.
• Build and maintain Stored Procedures, Views, and Functions for financial data transformation across SQL Server and Azure SQL.
• Design high-performance data schemas employing Star Schema and Snowflake Schema for efficient data warehousing and modeling.
• Develop enterprise data warehouse solutions on Azure Synapse with replicated distribution strategies.
• Create and manage Power BI dashboards, reports, and scorecards, integrating dataflows, datasets, and semantic models connected to Azure Synapse, Databricks, and other data sources.
• Develop dimensional models incorporating SCD Types 1, 2, 3, along with fact and aggregate tables.
• Utilize Power BI Desktop & Power BI Service for interactive data visualization, along with expertise in Power Query, Power Pivot, and Power View for ad-hoc analysis.
• Leverage Python (Pandas, NumPy) for data processing and analysis.
• Collaborate with business stakeholders to gather requirements and deliver actionable insights.
• Handle large-scale financial datasets with precision, ensuring high accuracy and timely delivery.

Preferred Skills & Knowledge:

• Exposure to Microsoft Fabric, OneLake, Azure Analysis Services (AAS), and SSAS Tabular Models for enterprise semantic layer development.
• Domain knowledge in Core Banking, Financial Services, Index & Benchmarking, Real Estate, Private Capital & Market.
• Strong communication skills to effectively liaise with business teams.
• Self-driven and capable of working independently in a high-volume data environment.