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Data Engineer (Snowflake)

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Valtech

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Location:
India , Bengaluru

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

As a Data Engineer, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 4+ years of experience, a growth mindset and a drive to make a lasting impact.

Job Responsibility:

  • Design and implement scalable, secure Snowflake data warehouses (multi-environment, role-based access, RBAC/ABAC, masking/row access).
  • Architect ELT pipelines using Fivetran/Stitch/Singer
  • extend with custom connectors when required.
  • Build and maintain dbt-based transformation layers (staging → marts → semantic models) with modular, test-driven designs.
  • Implement orchestration using Airflow/Prefect/Dagster for scheduling, dependencies, and retries.
  • Apply dimensional modeling, Data Vault, and star schema best practices for analytics at scale.
  • Optimize Snowflake performance: warehouse sizing, clustering/partitioning strategies, query tuning, caching, and cost controls (Resource Monitors, Query Acceleration).
  • Leverage advanced Snowflake features (Tasks, Streams, Time Travel, Data Sharing, External Tables/Iceberg, Snowpipe, object tagging).
  • Implement robust testing (dbt tests, Great Expectations) and proactive data validation frameworks.
  • Establish and enforce governance: data lineage, cataloging, PII classification, policies, RBAC, auditability.
  • Maintain documentation and lineage in tools like Alation/Collibra/DataHub
  • automate as part of CI/CD.
  • Set up CI/CD for dbt and data artifacts (Git-based workflows, environments, automated tests, PR checks).
  • Build Python utilities for ELT automation, data processing, backfills, and metadata operations.
  • Implement observability using Monte Carlo/Datafold (freshness, volume, schema change, anomaly monitoring).
  • Partner with analytics/data science teams to enable governed self-service (semantic/metric layers, certified datasets).
  • Translate stakeholder requirements into scalable data models and SLAs.
  • Champion DataOps and best practices across teams
  • conduct knowledge sessions.

Requirements:

  • Education: A Bachelor's or Master’s degree in computer science, Engineering, or a related technical field is typically required.
  • 4–7 years in data engineering/analytics engineering with cloud data warehousing focus.
  • Deep expertise in Snowflake: architecture, security (RBAC, masking, row access), performance tuning, cost optimization, and workload management.
  • Advanced dbt: macros, packages, refactoring layered models, exposures, tests (unique/not_null/relationships/custom), and best practices.
  • Strong ELT experience with Fivetran/Stitch/Singer
  • ability to build custom connectors if needed.
  • Excellent SQL and data modeling (dimensional modeling, star schema, Data Vault).
  • Proficient in Python for data processing, scripting, and automation.
  • Experience with Airflow/Prefect/Dagster for orchestration.
  • Solid CI/CD knowledge: Git workflows, environment promotion, automated testing.
  • Experience on at least one cloud (AWS/GCP/Azure) and their native data services (e.g., S3/GCS/ADLS, IAM, secrets).
  • Data governance, lineage, and data quality practices (Great Expectations/dbt tests).
  • Familiarity with BI tools (Tableau/Looker/Power BI) and how models feed them.

Nice to have:

  • Reverse ETL: Census, Hightouch, Polytomic.
  • Streaming platforms: Kafka, Kinesis, Pub/Sub
  • CDC patterns.
  • Data catalog: Alation, Collibra, DataHub.
  • Observability: Monte Carlo, Datafold (diffs, lineage impacts, anomaly detection).
  • Containerization & deployment: Docker, Kubernetes.
  • Concepts: DataOps, analytics engineering, data mesh, metric layer/semantic modeling.
  • Additional warehouses: BigQuery
  • transformation Dataform.
What we offer:
  • Flexibility, with hybrid work options (country-dependent)
  • Learning and development, with access to cutting-edge tools, training and industry experts.

Additional Information:

Job Posted:
February 20, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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