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.
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Design, configure, and optimize ingestion, transformation, and orchestration workflows using Matillion DPC where applicable.
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Design and implement scalable ELT pipelines using dbt on Snowflake, following industry-accepted best practices.
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Build and maintain data processing workloads on Azure Databricks (PySpark/Spark SQL), including notebooks, jobs, Delta Lake tables, and Lakehouse/medallion architectures.
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Build ingestion pipelines from various sources including relational databases, APIs, cloud storage, and flat files into Snowflake and Databricks (Delta Lake).
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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.
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Leverage orchestration tools (e.g., Airflow, dbt Cloud, Azure Data Factory, or Databricks Workflows) to schedule and monitor data pipelines.
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Apply dbt best practices: modular SQL development, testing, documentation, and version control.
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Perform performance optimizations in dbt/Snowflake/Databricks through clustering, query profiling, materialization, partitioning, caching, and efficient SQL/Spark design.
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Apply CI/CD and Git-based workflows for version-controlled deployments.
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Take complete ownership of assigned pipelines and deliverables — from design through production support — in line with Techdome's ownership culture.
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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.
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Collaborate with data analysts, data scientists, and data architects across onshore and offshore teams to understand requirements and deliver clean, validated datasets.
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Write well-documented, maintainable code using Git for version control and CI/CD processes.
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Participate in Agile ceremonies including sprint planning, stand-ups, and retrospectives.
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Support consulting engagements through clear documentation, demos, and delivery of client-ready solutions that reflect Techdome's commitment to excellence.
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1 to 4 years of experience in data engineering roles, with 6+ months of hands-on experience in Snowflake and dbt.
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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.
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Hands-on experience with Matillion Data Productivity Cloud (Matillion DPC) for data ingestion, transformation, or orchestration.
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Experience building and deploying dbt models in a production environment.
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Expert-level SQL and strong understanding of ELT principles; strong understanding of ELT patterns and data modelling (Kimball/Dimensional preferred).
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Familiarity with data quality and validation techniques: dbt tests, dbt docs, etc.
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Experience with Git, CI/CD, and deployment workflows in a team setting.
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Familiarity with orchestrating workflows using tools like dbt Cloud, Airflow, Azure Data Factory, or Databricks Workflows.
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Building robust and modular data pipelines using dbt and Databricks.
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Writing efficient SQL and PySpark for data transformation and performance tuning in Snowflake and Databricks.
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Managing environments, sources, and deployment pipelines in dbt.
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Strong proficiency with Snowflake: warehouse sizing, query profiling, data loading, and performance optimization.
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Strong proficiency with Azure Databricks: cluster configuration and sizing, Delta Lake optimization (OPTIMIZE, Z-ORDER, vacuum), Unity Catalog basics, and Spark job tuning.
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Experience working with cloud storage (Azure Data Lake, AWS S3, or GCS) for ingestion and external stages.
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Python / PySpark: For data transformation, notebook development, and automation on Databricks.
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SQL: Strong grasp of SQL for querying and performance tuning.
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Knowledge of modern data architecture concepts including layered architecture (staging intermediate marts) and Lakehouse/Medallion architecture.
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Familiarity with data quality, unit testing (dbt tests), and documentation (dbt docs).
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Understanding of access control within Snowflake (RBAC) and Databricks (Unity Catalog/workspace permissions), role hierarchies, and secure data handling.
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Familiarity with data privacy policies (GDPR basics) and encryption at rest/in transit.
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Version control using Git; experience with CI/CD practices in a data context.
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Monitoring and logging of pipeline executions, alerting on failures.
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Ownership mindset: take full responsibility for your work, from problem diagnosis to production delivery.
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Client-first communication: ability to present solutions confidently and handle client demos and discussions.
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Collaboration: work closely with onshore and offshore teams of analysts, data scientists, and architects — every voice is heard and respected.
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Ability to document pipelines and transformations clearly.
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Basic SSIS and Matillion.
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Comfort with ambiguity, competing priorities, and fast-changing client environments — we move fast and adapt faster.
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Passion for continuous learning and knowledge sharing (tech talks, meetups, internal upskilling).
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Experience in client-facing roles or consulting engagements.
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Exposure to AI/ML data pipelines and feature stores.
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Exposure to MLflow for basic ML model tracking (native to Databricks).
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Experience/exposure using data quality tooling.
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Certifications such as Snowflake SnowPro, Databricks Certified Data Engineer Associate, or dbt Certified Developer are a plus.
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Work on high-impact projects for global clients — from startups to Fortune 500 enterprises — across diverse industries.
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Be part of an inclusive culture that promotes open communication, teamwork, and respect for every voice.
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Grow with a company that invests in your professional development through mentorship, tech events, and hands-on exposure to cutting-edge data and AI technologies.
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Join a journey driven by insight and innovation — where we don't just solve problems, we push the boundaries of technology.
