Data Engineer

Role Overview Hotfoot Technology Solutions is seeking a skilled and hands-on Data Engineer to join its growing team in Chennai. In this role, you will design micro data lakes, define enterprise-level data strategies, and build scalable data pipelines that support both batch and real-time data ingestion. You will work closely with engineering and product teams to ensure that data architecture aligns seamlessly with overall business objectives. Key Responsibilities - Design and build micro data lakes specifically tailored to the lending domain - Define and implement enterprise data strategies covering data modelling, lineage, and governance - Architect and develop reliable data pipelines for both batch and real-time ingestion scenarios - Create strategies for extracting, transforming, and storing data from diverse sources including APIs, PDFs, logs, and databases - Establish and enforce best practices for data quality, metadata management, and data lifecycle control - Evaluate and integrate modern data platforms and tools such as Databricks, Spark, Kafka, Snowflake, AWS, GCP, and Azure - Mentor junior and mid-level data engineers and champion engineering excellence across data practices - Collaborate cross-functionally to deliver differentiated data products in a hands-on capacity Required Qualifications - Minimum 4 years of hands-on experience in data engineering - Deep understanding of structured and unstructured data ecosystems - Proficiency in ETL, ELT, stream processing, querying, and data modelling techniques - Strong command over tools and languages including Spark, Kafka, Airflow, SQL, Python, Amundsen, and Glue Catalog - Expertise in cloud-native platforms such as AWS, Azure, or GCP - Solid knowledge of data governance, privacy regulations, and compliance standards - Strategic thinking combined with the ability to execute implementation tasks hands-on Why Join Us Hotfoot Technology Solutions offers an exciting opportunity to work on impactful data projects within the fintech and lending space. You will be part of a collaborative team that values engineering excellence and innovation in data architecture.

- 4+ years of data engineering experience - Hands-on expertise with Spark, Kafka, Airflow, and Python - Experience with ETL, ELT, and stream processing - Proficiency in SQL and data modelling - Cloud platform experience with AWS, Azure, or GCP - Knowledge of data governance and compliance standards - Familiarity with tools like Amundsen and Glue Catalog - Exposure to lending domain or fintech environments is a plus - Experience with ML pipelines or AI integrations is a plus

- Full-time permanent role - Opportunity to work on cutting-edge data platforms - Collaborative and growth-oriented work environment - Mentorship and leadership opportunities