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StatusNeo - Data Engineer

Reposted 16 Days Ago
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In-Office
Bengaluru, Bengaluru Urban, Karnataka, IND
Senior level
In-Office
Bengaluru, Bengaluru Urban, Karnataka, IND
Senior level
Design, build, and maintain large-scale data pipelines and ETL/ELT workflows using Spark and Scala. Implement data models and warehousing on Snowflake and cloud (AWS/GCP). Ensure data quality, governance, security, and performance optimization while collaborating with data scientists, analysts, DevOps, and stakeholders.
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Job Title: Data Engineer/ Sr. Data Engineer

Experience Level: 3-6 Years 

Work Mode- Hybrid ( 2 PM to 11 PM )

Location: Bangalore/Gurgaon

Job Type: Full-Time

Company- StatusNeo

About the RoleWe’re looking for a Data Engineer who thrives on solving complex data challenges, building scalable pipelines, and delivering reliable insights that drive business decisions. The ideal candidate will bring hands-on expertise in cloud data platforms (AWS, GCP), Snowflake, Big Data ecosystems, and distributed computing using Spark and Scala. Key Responsibilities
  • Design, build, and maintain data pipelines for large-scale ingestion, transformation, and integration from multiple data sources.

  • Develop and optimize ETL/ELT workflows leveraging tools such as Spark, Scala, and SQL.

  • Implement data models and data warehousing solutions on Snowflake and cloud environments (AWS/GCP).

  • Work closely with data scientists, analysts, and business stakeholders to deliver high-quality, production-ready data solutions.

  • Manage data quality, governance, and security across environments.

  • Optimize performance of data pipelines, focusing on scalability, efficiency, and cost optimization in cloud setups.

  • Collaborate with DevOps teams for CI/CD deployment and monitoring of data solutions.

  • Technical Skill Set (Must Have)

    • Programming Languages: Scala, SQL

    • Big Data Frameworks: Apache Spark, Hadoop ecosystem

    • Cloud Platforms: AWS (S3, EMR, Glue, Redshift, Lambda) and/or GCP (BigQuery, Dataflow, Dataproc, Composer)

    • Data Warehouse: Snowflake (data modeling, performance tuning, query optimization)

    • ETL Tools: Spark-based ETL or Airflow/Glue/Composer

    • Version Control & CI/CD: Git, Jenkins, or equivalent

    • Data Formats: Parquet, Avro, ORC, JSON, CSV

      Good to Have
      • Knowledge of Python for data scripting and automation.

      • Familiarity with containerization (Docker, Kubernetes).

      • Experience with data cataloging and metadata management tools.

      • Exposure to streaming frameworks (Kafka, Pub/Sub).

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