Full Stack Data Engineer

We are looking for a Full Stack Data Engineer with strong experience in financial data, data analytics, dashboards, backend systems, and data pipelines. The candidate should be able to work across the complete data stack, from data ingestion and processing to APIs, databases, analytics, and frontend dashboards.

Key Responsibilities

• Build and maintain data pipelines for financial and business data.
• Work with transaction, payment, revenue, settlement, customer, and financial datasets.
• Develop ETL and ELT pipelines for structured and unstructured data.
• Design and optimize SQL databases and data models.
• Build backend APIs to expose processed data to applications and dashboards.
• Develop interactive dashboards for financial reporting, KPIs, transactions, revenue, and operational metrics.
• Work with React.js, Next.js, or similar frontend technologies.
• Create data visualizations, charts, reports, and analytics interfaces.
• Implement data validation, reconciliation, and quality checks.
• Handle large datasets and optimize queries and data processing.
• Integrate data from APIs, databases, CSV files, payment systems, and third party platforms.
• Build monitoring and alerting for data pipelines and critical financial processes.
• Ensure data security, access control, and accuracy for sensitive financial information.
• Work closely with product, finance, engineering, and business teams.

Required Skills

• 4+ years of experience in Data Engineering, Full Stack Development, or a similar role.
• Strong Node.js experience.
• Advanced SQL and database optimization skills.
• Experience with PostgreSQL, MySQL, MongoDB, or similar databases.
• Strong experience working with financial or transactional data.
• Experience building financial, analytics, or business dashboards.
• React.js or Next.js experience.
• Experience developing REST APIs.
• Experience with ETL and ELT pipelines.
• Experience with data warehouses such as BigQuery, Snowflake, Redshift, or Databricks.
• Experience with AWS, Azure, or Google Cloud.
• Strong understanding of data modeling, indexing, aggregation, and query optimization.
• Experience with Git and CI/CD.

Good to Have

• Experience with payment gateways, banking systems, fintech platforms, or accounting systems.
• Experience with reconciliation and settlement data.
• Apache Airflow.
• Apache Spark or PySpark.
• Kafka or other streaming technologies.
• dbt.
• Redis and Elasticsearch.
• Docker and Kubernetes.
• Experience with Power BI, Metabase, Tableau, or similar BI tools.
• Experience building real time financial dashboards.
• Experience working with AI or ML data pipelines.

Ideal Candidate

The ideal candidate can take a financial data requirement from start to finish. They should be comfortable working with raw transaction data, building the processing pipeline, designing the database, developing APIs, creating dashboards, and deploying the complete solution.

Pay: ₹70,000.00 - ₹100,000.00 per month

Work Location: In person