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▷ (3 Days Left) Data Engineer

▷ (3 Days Left) Data Engineer

SolarSquareIndia
3 hours ago
Job description

Job Description : Data Engineer

As a Data Engineer, you will own the end-to-end lifecycle of our data infrastructure. You will

design and implement robust, scalable data pipelines and architect modern data solutions

using a best-in-class technology stack. Your work will transform raw, messy data into clean,

reliable, and actionable data products that power decision-making across the business.

You’ll collaborate cross-functionally with product managers, data analysts, data scientists,

and software engineers to understand data needs and deliver high-performance data

solutions. Your impact will be measured by how effectively data is delivered, modeled, and

leveraged to drive business outcomes.

Key Responsibilities :

  • Architect & Build : Design, implement and manage cloud-based data platform using a

modern ELT (Extract, Load, Transform) approach.

  • Data Ingestion : Develop and maintain robust data ingestion pipelines from a variety of sources, including operational databases (MongoDB, RDS), real-time IoT streams, and
  • third-party APIs using services like AWS Kinesis / Lambda or Azure Event Hubs / Functions.

  • Data Lake Management : Build and manage a scalable and cost-effective data lake on
  • AWS S3 or Azure Data Lake Storage (ADLS Gen2), using open table formats like Apache

    Iceberg or Delta Lake.

  • Data Transformation : Develop, test, and maintain complex data transformation models using dbt. Champion a software engineering mindset by applying principles of version control (Git), CI / CD, and automated testing to all data logic.
  • Orchestration : Implement and manage data pipeline orchestration using modern tools like Dagster, Apache Airflow, or Azure Data Factory.
  • Data Quality & Governance : Establish and enforce data quality standards. Implement automated testing and monitoring to ensure the reliability and integrity of all data assets.
  • Performance & Cost Optimization : Continuously monitor and optimize the performance and cost of the data platform, ensuring our serverless query engines and storage layers are used efficiently.
  • Collaboration : Work closely with data analysts and business stakeholders to
  • understand their needs, model data effectively, and deliver datasets that power our BI

    tools (Metabase, Power BI).

    Required Skills & Experience (Must-Haves) :

  • 3+ years of professional experience in a data engineering role.
  • Expert-level proficiency in SQL and the ability to write complex, highly-performant queries.
  • Proficient in Python based data cleaning packages and tools. Experience in python is a must.
  • Hands-on experience building data solutions on a major cloud provider (AWS or Azure), utilizing core services like AWS S3 / Glue / Athena or Azure ADLS / Data Factory / Synapse.
  • Proven experience building and maintaining data pipelines in Python.
  • Experience with NoSQL databases like MongoDB, including an understanding of its data modeling, aggregation framework, and query patterns.
  • Deep understanding of data warehousing concepts, including dimensional modeling, star / snowflake schemas, and data modeling best practices.
  • Hands-on experience with modern data transformation tools, specifically dbt.
  • Familiarity with data orchestration tools like Apache Airflow, Dagster, or Prefect.
  • Proficiency with Git and experience working with CI / CD pipelines for data projects.
  • Preferred Skills & Experience (Nice-to-Haves) :

  • Experience with real-time data streaming technologies, specifically AWS Kinesis or Azure Event Hubs.
  • Experience with data cataloging and governance tools (e.g., OpenMetadata, DataHub, Microsoft Purview).
  • Knowledge of infrastructure-as-code tools like Terraform or CloudFormation.
  • Experience with containerization technologies (Docker, Kubernetes).
  • Create a job alert for this search

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