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Cloud • Fintech • Information Technology • Machine Learning • Software • App development • Generative AI
Lead architecture, design, development, and delivery of enterprise data platform components. Build and optimize ETL/ELT pipelines, data models, and warehouses (Snowflake). Mentor engineers, drive data governance, ensure performance, security, and scalability, and collaborate cross-functionally to adopt best practices and new tools.
Top Skills:
Sql,Snowflake,Python,Java,Rdbms,Nosql,Elt/Etl Tools,Stored Procedures,Ctes,Udfs,Cloud-Native (Google Cloud Preferred),Data Warehouse
Fintech • Professional Services • Consulting • Energy • Financial Services • Cybersecurity • Generative AI
Design, build, and operate scalable ETL/ELT pipelines using PySpark and AWS data services. Orchestrate workflows with Apache Airflow, implement AWS Glue jobs and Data Catalog, manage Lake Formation permissions, publish datasets for BI, and deliver QuickSight visualizations while ensuring data quality and performance.
Top Skills:
Pyspark,Apache Airflow,Aws Glue,Aws Lake Formation,Aws Glue Data Catalog,Amazon Quicksight
Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
No role-specific responsibilities provided in the posting. Typically, a Unit Manager - Data Governance leads the data governance function: defining and enforcing data policies, managing data quality and metadata, coordinating stakeholders, ensuring regulatory compliance, and supervising a team to implement governance processes.
Saaf Finance is building the AI workforce for the mortgage industry. We are an AI startup integrated with a top-10 mortgage lender, American Heritage Lending (AHL). Together we are combining AHL’s 15+ years of mortgage origination expertise with the power of AI-native innovation to redefine what’s possible in mortgage lending.
This is a rare opportunity to join at a pivotal moment. You’ll build and own the data pipelines, warehouses, and analytics infrastructure that power AI-driven underwriting, automation, and real-time financial decision-making at scale, working directly with founders and engineering leadership to shape how AI transforms a $17 trillion industry.
As a Data Engineer you will be part of a focused product and technology team with the backing of a $10 Billion+ New York-based investment fund—giving us stability, scale and resources of an established institution with the speed, innovation and ownership of a startup.
If you thrive in fast-moving environments, enjoy working with complex data systems, and want to see your work power real financial decisions for thousands of borrowers, this role is for you.
Key Responsibilities- Data Pipeline Development – Design, implement, and maintain ETL/ELT pipelines for structured and unstructured datasets from internal and external sources.
- Data Warehousing – Build and optimize warehouses and marts (Snowflake, BigQuery, or similar) for analytics, reporting, and product use cases.
- Integration – Ingest data from APIs, SaaS platforms such as CRM and financial data APIs, and internal systems into the core data platform.
- Data Modeling: Design, implement, and maintain conceptual, logical, and physical data models to ensure scalable, consistent, and high-quality datasets for downstream analytics and applications
- Data Quality and Governance – Implement validation, schema management, and robust documentation to ensure data accuracy and compliance.
- Performance Optimization – Monitor and fine-tune pipeline and warehouse performance for scalability and cost efficiency.
- Security and Compliance – Apply data security and privacy controls aligned with financial regulatory requirements, ensuring full traceability of every transformation.
- Analytics Enablement – Provide clean, consistent datasets for analysts, product managers, and operational teams to support fast, data-driven decisions.
Requirements
Technical Expertise
- Strong SQL and Python development skills for data transformation and automation.
- Experience with modern ETL/ELT frameworks such as dbt.
- Proficiency with cloud platforms (AWS preferred) and serverless data services.
- Strong experience with data warehouse technologies (Snowflake preferred).
- Skilled in API integrations and ingestion from third-party systems.
Data Operations
- Proficient in data modeling (Kimball/Star schema, Data Vault).
- Experience implementing CI/CD practices for data workflows.
- Ability to set up logging, monitoring, and alerting for data jobs.
- Experience building agentic workflows and orchestrating multi-step automated processes that act on data in real time.
- Familiarity with data engineering patterns and infrastructure required for the recent wave of AI-powered tools and automation platforms.
- Experience working with financial datasets and APIs in a high-compliance environment.
- Understanding of data privacy regulations such as GDPR and CCPA.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- 3+ years in a data engineering or similar backend data-focused role.
- Proven track record of delivering production-grade data pipelines at scale.
- Experience collaborating closely with product managers, data scientists, and full stack engineers.
- Startup mindset: hands-on, resourceful, and comfortable operating in a fast-paced environment.
Benefits
- Competitive salary
- High ownership from day one — your work will directly shape core systems and products
- Fast-paced environment with quick decision cycles and minimal bureaucracy
- Remote-first team with flexibility on work hours and location
- Direct access to founders and cross-functional teams — no layers, no silos
- Clear expectations, regular feedback, and support for professional growth
- Work on real problems in a complex, high-impact industry
What you need to know about the Chennai Tech Scene
To locals, it's no secret that South India is leading the charge in big data infrastructure. While the environmental impact of data centers has long been a concern, emerging hubs like Chennai are favored by companies seeking ready access to renewable energy resources, which provide more sustainable and cost-effective solutions. As a result, Chennai, along with neighboring Bengaluru and Hyderabad, is poised for significant growth, with a projected 65 percent increase in data center capacity over the next decade.
