Role : Data Engineer (Snowflake / DBT / Python / PySpark)

Experience : 6+ years in data engineering / cloud data warehousing

Location : Bangalore, India (Hybrid / Onsite as required)

Employment Type : Full-time

Notice Period : Immediate to 30 days preferred

About the Role :

We are looking for a hands-on Data Engineer with strong expertise in Snowflake, DBT, Python, and PySpark to design, build, and optimize scalable ELT data pipelines and cloud-based analytics platforms. You will work with enterprise clients across domains such as healthcare, manufacturing, and retail, delivering high-performance data integration, transformation, and analytics solutions on AWS.

About organisation :

We are an Indian IT services and consulting firm based in Bengaluru. Founded in 2024, the company delivers digital transformation solutions to global B2B clients.

Core Capabilities :

- Artificial Intelligence : Building AI/ML models and automated chatbots.

- Data & Cloud : Managing data engineering and cloud migrations.

- Automation : Implementing Robotic Process Automation (RPA) workflows.

- Core Focus : Specialises in AI/ML solutions, cloud platforms, data engineering, and automation.

- Target Market : Modernises operations primarily for business-to-business (B2B) clients globally.

- Footprint : Operates from India but serves customers across the US and UAE.

Key Responsibilities :

- Design and implement end-to-end ELT data pipelines using Snowflake and DBT for enterprise analytics workloads.

- Develop modular, well-tested DBT models (staging, intermediate, marts) with incremental loading strategies, snapshots, and SCD Type-2 logic for historical dimensions.

- Build and maintain large-scale distributed data processing jobs using PySpark for batch and near real-time transformation workloads.

- Write production-grade Python code for data validation, reconciliation, automation, and orchestration of pipeline workflows.

- Automate cloud data ingestion using AWS S3, Snowpipe, Streams and Tasks for incremental and near real-time processing.

- Design fact and dimension tables following star and snowflake schema architecture for enterprise reporting.

- Optimize Snowflake query performance and warehouse utilization to reduce compute cost - clustering, pruning, caching, and SQL tuning.

- Implement CI/CD and version control practices (Git) for DBT projects and data pipeline code.

- Ensure data quality, testing, and documentation across all pipeline layers (DBT tests, custom validation frameworks).

- Collaborate with BI/analytics teams (Power BI) to deliver analytics-ready datasets and support data validation for dashboards.

Must-Have Skills :

- DBT : Strong hands-on experience building transformation workflows - models, macros, Jinja templating, incremental models, tests, snapshots, and documentation.

- Python : Advanced scripting for data processing, automation, API integration, and validation frameworks (pandas, boto3, etc.).

- PySpark : Experience developing and tuning Spark jobs - DataFrames, partitioning, joins, window functions, and performance optimization on large datasets.

- Snowflake : Deep knowledge of architecture, virtual warehouses, Snowpipe, Streams & Tasks, Time Travel, zero-copy cloning, and performance tuning.

- SQL : Expert-level query writing, optimization, and data modeling (star/snowflake schemas, SCD handling).

- AWS : Working experience with S3, IAM, EC2, and event-driven ingestion patterns.

Good-to-Have Skills :

- Experience with ETL tools such as Talend, Airflow, or similar orchestration frameworks.

- Exposure to Databricks, EMR, or Glue for Spark workloads.

- Familiarity with Power BI or other visualization tools for data validation and QA support.

- Snowflake SnowPro Core certification (or equivalent).

- Experience in healthcare, pharma, manufacturing, or supply-chain analytics domains.

Qualifications :

- Bachelor's degree in Engineering, Computer Science, or a related field (B.Tech / B.E. / MCA).

- 6+ years of professional experience in data engineering, with at least 2 years on Snowflake and DBT.

What We Look For :

- Strong analytical and problem-solving skills with a focus on data quality and reliability.

- Ability to work independently, own deliverables end-to-end, and communicate clearly with client stakeholders.

- Quick learner of modern cloud and data engineering technologies