Role Overview

We are looking for an experienced and results-driven Data Engineer to join our growing Data Engineering practice. The ideal candidate will be proficient in building scalable, high-performance data transformation pipelines using Snowflake, Azure Databricks, and dbt, and will thrive in Techdome's fast-paced, client-facing consulting setting. In this role, you will be instrumental in ingesting, transforming, and delivering high-quality data to enable data-driven decision-making across our clients' organizations — owning your deliverables like a true Tech Doctor.

Key Responsibilities

Design, configure, and optimize ingestion, transformation, and orchestration workflows using Matillion DPC where applicable.
Design and implement scalable ELT pipelines using dbt on Snowflake, following industry-accepted best practices.
Build and maintain data processing workloads on Azure Databricks (PySpark/Spark SQL), including notebooks, jobs, Delta Lake tables, and Lakehouse/medallion architectures.
Build ingestion pipelines from various sources including relational databases, APIs,



cloud storage, and flat files into Snowflake and Databricks (Delta Lake).
Implement data modelling and transformation logic to support layered architecture (staging, intermediate, and mart layers, or medallion architecture) to enable reliable and reusable data assets.
Leverage orchestration tools (e.g., Airflow, dbt Cloud, Azure Data Factory, or Databricks Workflows) to schedule and monitor data pipelines.
Apply dbt best practices: modular SQL development, testing, documentation, and version control.
Perform performance optimizations in dbt/Snowflake/Databricks through clustering, query profiling, materialization, partitioning, caching, and efficient SQL/Spark design.
Apply CI/CD and Git-based workflows for version-controlled deployments.
Take complete ownership of assigned pipelines and deliverables — from design through production support — in line with Techdome's ownership culture.
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📌 Data Engineer (Hyderabad)
🏢 Techdome
📍 Hyderabad