Senior Software Developer
On-siteBengaluru, Karnataka, India
Job Summary
Design, build, and maintain scalable ETL/ELT pipelines on Databricks and Spark that ingest structured, semi-structured, and unstructured data into high-quality, AI-consumable datasets for Search, Recommendations, and Supply Chain analytics. Develop robust data models including fact/dimension structures, SCDs, and CDC pipelines while implementing data versioning, partitioning, and clustering strategies. Partner with Data Science teams to prepare feature pipelines, embeddings, and semantic layers for ML model consumption and operationalization. Implement data quality checks, observability, and governance frameworks to ensure SLA/SLO adherence across the data ecosystem. Mentor junior engineers, review code designs, and collaborate cross-functionally to translate ambiguous business requirements into production-grade data solutions. This role supports Tecsys's 24/7 global support model from our Bangalore office, requiring 6–8+ years of experience in data engineering with a focus on reliability and engineering best practices.
Required Qualifications
- Advanced proficiency in SQL and Python, with strong focus on query optimization, cost efficiency, and large-scale data processing
- Hands-on experience with Databricks, Apache Spark, and distributed processing frameworks
- Strong experience building ETL/ELT pipelines and workflow orchestration (Airflow, Dagster, or similar)
- Solid understanding of Data Lake / Lakehouse architectures, storage formats (Parquet, Delta/Iceberg), partitioning, clustering, and performance tuning
- Deep expertise in data modeling: fact/dimension models, SCDs, wide tables, CDC, data versioning, and incremental processing
- Experience with event-driven and streaming architectures (Kafka, Pub/Sub, Kinesis) applied pragmatically alongside batch where needed
- Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and cloud data warehouses (Snowflake, BigQuery, Redshift)
- Familiarity with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code for data systems
- Experience building production-grade data systems with strong data quality, observability, and SLA/SLO practices
- Familiarity with metadata management, data lineage, and data discovery tools (e.g., DataHub, OpenMetadata, Amundsen)
- Bachelor's or Master's in Computer Science, Engineering, or related field — or equivalent practical experience
- 6–8+ years of experience in Data Engineering, building and operating production-grade data platforms at scale
- Demonstrated experience delivering data solutions across analytics, ML, or product-facing domains
- Proven ability to translate ambiguous business requirements into scalable data models and systems
- Ownership mindset — drives features end-to-end with strong communication and collaboration skills
- This role will require you to be based in Bengaluru
Desired Qualifications
- Experience enabling AI/ML use cases from a data perspective — preparing datasets, feature stores, embeddings, or semantic/metric layers (dbt, Cube, LookML)
- Exposure to BI tools (Power BI, Tableau, Looker) and KPI modeling for business stakeholders
- Experience in Supply Chain, Logistics, or Healthcare supply chain analytics is a strong plus
- Familiarity with domains such as Search, Recommendations, or Marketing analytics
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