Data Engineer (Snowflake + Azure Databricks + dbt/Matillion)

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 environment. 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.
• Contribute to Techdome’s internal knowledge base of dbt macros, Databricks patterns, conventions, and testing frameworks; participate in internal tech talks and knowledge-sharing sessions.
• Collaborate with data analysts, data scientists, and data architects across onshore and offshore teams to understand requirements and deliver clean, validated datasets.
• Write well-documented, maintainable code using Git for version control and CI/CD processes.
• Participate in Agile ceremonies including sprint planning, stand-ups, and retrospectives.
• Support consulting engagements through clear documentation, demos, and delivery of client-ready solutions that reflect Techdome’s commitment to excellence.

Required Qualifications

• 1 to 4 years of experience in data engineering roles, with 6+ months of hands-on experience in Snowflake and dbt.
• Mandatory: Hands-on experience with Azure Databricks — developing and deploying pipelines using PySpark/Spark SQL, Delta Lake, notebooks, clusters, and Databricks Workflows/Jobs in a production environment.
• Hands-on experience with Matillion Data Productivity Cloud (Matillion DPC) for data ingestion, transformation, or orchestration.
• Experience building and deploying dbt models in a production environment.
• Expert-level SQL and strong understanding of ELT principles; strong understanding of ELT patterns and data modelling (Kimball/Dimensional preferred).
• Familiarity with data quality and validation techniques: dbt tests, dbt docs, etc.
• Experience with Git, CI/CD, and deployment workflows in a team setting.
• Familiarity with orchestrating workflows using tools like dbt Cloud, Airflow, Azure Data Factory, or Databricks Workflows.

Core Competencies

Data Engineering and ELT Development

• Building robust and modular data pipelines using dbt and Databricks.
• Writing efficient SQL and PySpark for data transformation and performance tuning in Snowflake and Databricks.
• Managing environments, sources, and deployment pipelines in dbt.

Cloud Data Platform Expertise

• Strong proficiency with Snowflake: warehouse sizing, query profiling, data loading, and performance optimization.
• Strong proficiency with Azure Databricks: cluster configuration and sizing, Delta Lake optimization (OPTIMIZE, Z-ORDER, vacuum), Unity Catalog basics, and Spark job tuning.
• Experience working with cloud storage (Azure Data Lake, AWS S3, or GCS) for ingestion and external …