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Sr Data Engineer

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Onsite

Sr Data Engineer

Zeta Global

Sr Data Engineer

Skills

SQL QueriesMongoDBTableauPythonPostgreSQLAWS LambdaKafkaDatabricksDatadogData AnalysisMachine LearningAIScalaAWSdbtApache AirflowTerraform

1 month ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Onsite

Published on:

18 September 2026

What they need


What You''ll Do

  • Own and evolve our Databricks Lakehouse platform Unity Catalog governance, Delta Lake table management, and Lakeflow Declarative Pipelines.
  • Design and build reliable, scalable data pipelines using Apache Spark and dbt for batch and near-real-time processing.
  • Stream and ingest data at scale via Kafka; orchestrate workflows with Airflow.
  • Partner with the integrations team to onboard new data sources and support AI/ML and analytics use cases.
  • Own data quality and observability end-to-end using Datadog; proactively identify and resolve discrepancies across data layers.
  • Manage infrastructure as code using Terraform; ensure platform reliability and cost efficiency on AWS.
  • Build and maintain MongoDB and PostgreSQL data stores; define schema standards and access patterns.
  • Deliver data products surfaced in Tableau; collaborate with analytics and product teams on reporting requirements.
  • Mentor engineers, lead code reviews, and drive engineering best practices across the team.
  • Participate in hiring and onboarding of new team members. Required
  • Deep hands-on expertise with Databricks Unity Catalog, Delta Lake, and Lakeflow Declarative Pipelines.
  • Strong Apache Spark experience tuning, optimization, and production operations.
  • Proficiency in Scala (required) and Python for data pipeline development.
  • Experience with Kafka for real-time data ingestion and streaming architectures.
  • Solid dbt skills for SQL-based transformation and data modeling.
  • Familiarity with Airflow for workflow orchestration.
  • Infrastructure experience with Terraform and AWS (S3, IAM, networking fundamentals).
  • Experience with MongoDB and PostgreSQL for operational and analytical workloads.
  • Strong communication skills able to translate complex technical concepts for non-technical audiences.

Keywords:

Data Platform: Databricks (Unity Catalog, Delta Lake, Lakeflow Declarative Pipelines), Apache Spark

Databases: MongoDB, PostgreSQL

Cloud: AWS (S3, EMR, Lambda, Glue, IAM, VPC)

Streaming & Messaging: Apache Kafka

Orchestration: Apache Airflow

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