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Data Science4 days agoOn-site

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SDE 2

sparkpysparkscalaflinkairflowicebergdeltahudikubernetesgcpawsazurepythonci/cdgitterraformhelmkafkadbtgreat expectationsprometheusgrafanaopenmetadatadatahubdata platformdata engineeringstreamingbatch processing

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Mid-level

Years experience

3-5

Location

Lucknow, India

Full job description

SDE II - Data Platform role in Lucknow. Responsibilities include building and maintaining scalable batch and streaming data pipelines using Spark and Flink, developing integrations with Airflow, Iceberg, and cloud platforms, applying best practices in data modeling and query optimization, supporting Kubernetes workloads, optimizing pipelines for performance and cost, implementing monitoring and data quality checks, and participating in on-call incident resolution. Requires 3-6 years of experience in data/platform engineering, strong SQL and data modeling skills, hands-on Spark experience, familiarity with Airflow and data lake formats, knowledge of Kubernetes and cloud platforms (GCP/AWS/Azure), Python programming skills, and exposure to CI/CD, Git, and infrastructure as code tools. Good to have experience with Kafka, DBT, Great Expectations, observability tools, and metadata/catalog tools. Benefits include continuous learning and career progression programs, equal employment opportunity, and accommodations for disabilities.

What you'll do

  • Build and maintain scalable data pipelines (batch & streaming) using Spark/Flink
  • Develop integrations across Airflow, Iceberg, and cloud platforms
  • Apply best practices in data modeling, partitioning, and query optimization
  • Support Kubernetes-based data platform workloads and troubleshoot issues
  • Optimize pipelines for performance, cost, and reliability
  • Implement monitoring, logging, and data quality checks
  • Participate in on-call and incident resolution

Requirements

  • 3–6 years in data/platform engineering
  • Strong fundamentals: SQL, data modeling, partitioning, optimization
  • Hands-on with Spark (PySpark/Scala); exposure to Flink is a plus
  • Experience with Airflow (or similar orchestration tools)
  • Familiarity with data lake formats (Iceberg/Delta/Hudi)
  • Working knowledge of Kubernetes & cloud (GCP/AWS/Azure)
  • Programming: Python (must-have), Scala (good-to-have)
  • Exposure to CI/CD, Git, and IaC (Terraform/Helm basics)

Tech stack

SparkPySparkScalaFlinkAirflowIcebergDeltaHudiKubernetesGCPAWSAzurePythonCI/CDGitTerraformHelmKafkaDBTGreat ExpectationsPrometheusGrafanaOpenMetadataDataHub

Benefits

Continuous learning and career progression through InMobi Live Your Potential programEqual Employment Opportunity employerReasonable accommodations for qualified individuals with disabilities

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