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Data Engineer - Remote (US) - Full Time Only

Remote · USA Full-time New today

Role: Data Engineer Location: Remote (Candidate should be comfortable to follow PST Time Zone) Job Type: Full Time Note: Active LinkedIn ID is a must and match with the resume Must Have Skills: Azure Databricks, Apache Spark, Snowflake, Data Governance, Unity Catalog, dBT, Microsoft Purview, Kafka, SQL, Python Experience and Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 10+ years of experience in data engineering / data architecture, with deep hands-on expertise in Microsoft Azure.

  • Expert-level experience with Azure Databricks and Apache Spark(PySpark, Spark SQL)
  • Delta Lake
  • Unity Catalog
  • Job orchestration and performance tuning
  • Strong experience with Snowflake on Azure, including:
  • Schema and data model design
  • Performance and cost optimization
  • RBAC, Streams, and Tasks
  • DBT (Core or Cloud) expertise:
  • Project structure and best practices
  • Tests, exposures, macros
  • Strong fundamentals in SQL and Python
  • Proven experience building ETL/ELT pipelines using:
  • Azure Data Factory (ADF)
  • Azure Synapse / Microsoft Fabric pipelines
  • Familiarity with streaming platforms such as Event Hubs and/or Kafka
  • Solid understanding of:
  • Lakehouse and data warehousing architectures
  • Dimensional modeling
  • Medallion architecture patterns
  • Data quality frameworks
  • Strong knowledge of security and governance, including:
  • Microsoft Purview (catalog, lineage)
  • Data masking and PII handling
  • Managed identities
  • Private networking
  • Excellent communication and documentation skills, with the ability to:
  • Create architecture and design documents
  • Present to both technical and business stakeholders
  • Consulting / agency experience, with the ability to lead multiple concurrent projects
  • Willingness to travel as required Nice to Have:
  • Experience with Azure ML, feature stores, or serving ML pipelines from Databricks or Snowflake
  • Infrastructure as Code (IaC) using Terraform or Bicep
  • Containerization experience with Docker
  • Observability and data quality tooling, such as:
  • Great Expectations / Delta Expectations
  • Databricks Quality Flows
  • Monte Carlo
  • Datadog Preferred Certifications:
  • Databricks Certified Data Engineer Professional or Databricks Architect
  • Microsoft Azure:
  • DP-203 Azure Data Engineer
  • Azure Solutions Architect Expert
  • Azure Security Engineer Associate
  • Snowflake:
  • SnowPro Core
  • SnowPro Advanced Job Description / Responsibilities:
  • Partner with client stakeholders to translate business objectives into scalable Azure data architectures and delivery roadmaps
  • Architect and implement lakehouse and data warehouse solutions using:
  • Azure Databricks (Delta Lake, Unity Catalog)
  • Databricks Bundle
  • Snowflake on Azure
  • dbt (Core / Cloud)
  • ADLS Gen2
  • Medallion architecture patterns
  • Design and build robust ingestion and transformation pipelines using:
  • Azure Data Factory (ADF)
  • Microsoft Fabric / Synapse pipelines
  • Orchestrate ELT workflows using:
  • Databricks Jobs
  • Delta Live Tables
  • dbt models
  • Establish best practices for performance and cost optimization, including:
  • Cluster sizing and autoscaling
  • Photon and SQL Warehouses
  • Snowflake virtual warehouses
  • Caching, file layout optimization, Z-ordering
  • Drive observability and monitoring using:
  • Azure Monitor
  • Log Analytics
  • Databricks metrics
  • Implement robust data governance and security using:
  • Azure Authentication
  • Unity Catalog
  • RBAC / ABAC
  • Managed identities
  • Private Endpoints and VNet injection
  • Azure Key Vault backed secrets
  • Lead code and design reviews, setting standards for:
  • PySpark, SQL, and dbt
  • Unit and integration testing
  • Data quality checks (expectations and constraints)
  • Implement CI/CD pipelines using Azure DevOps or GitHub Actions
  • Guide multi-domain programs (Healthcare, Retail, BFSI, or similar)
  • Mentor data engineers and ensure high-quality, production-ready deliverables
  • Evangelize solutions through:
  • Clear documentation
  • Reference architectures
  • Executive and stakeholder presentations Remote About the Company: Saransh Inc Apply tot his job

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