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Data Engineer

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Onsite

Data Engineer

Talent21

Data Engineer

Skills

Google Cloud PlatformSQL QueriesDockerPythonProduct ManagementKafkaDatabricksLinuxKubernetesPySparkApache AirflowKanbanAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Onsite

Published on:

3 September 2026

What they need


Data Engineer
Hyderabad, Telangana, India
Job Description

Must have Skills:

  • 3+ yrs. Development experience with Spark (PySpark), Python and SQL.

  • Extensive knowledge building data pipelines

  • Hands on experience with Databricks Devlopment

  • Strong experience with

  • Strong experience developing on Linux OS.

  • Experience with scheduling and orchestration (e.g. Databricks Workflows,airflow, prefect, control-m).

Good to have skills:

  • Solid understanding of distributed systems, data structures, design principles.

  • Agile Development Methodologies (e.g. SAFe, Kanban, Scrum).

  • Comfortable communicating with teams via showcases/demos.

  • Play key role in establishing and implementing migration patterns for the Data Lake Modernization project.

  • Actively migrate use cases from our on premises Data Lake to Databricks on GCP.

  • Collaborate with Product Management and business partners to understand use case requirements and reporting.

  • Adhere to internal development best practices/lifecycle (e.g. Testing, Code Reviews, CI/CD, Documentation) .

  • Document and showcase feature designs/workflows.

  • Participate in team meetings and discussions around product development.

  • Stay up to date on industry latest industry trends and design patterns.

  • 3+ years experience with GIT.

  • 3+ years experience with CI/CD (e.g. Azure Pipelines).

  • Experience with streaming technologies, such as Kafka, Spark.

  • Experience building applications on Docker and Kubernetes.

  • Cloud experience (e.g. Azure, Google).

Required Skills Linux OS, SQL, Spark PySpark Python, Databricks Devlopment, Docker, Agile, Azure Pipelines, GIT, Workflows airflow prefect control, Kafka Spark, Kubernetes, Azure Google, SAFe Kanban Scrum

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