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Data Engineer - Python / SQL

Data Engineer - Python / SQL

Hashone CareersBangalore
17 days ago
Job description

Description :

We are seeking a skilled and motivated Data Engineer with 3 to 5 years of experience to join our growing team.

The ideal candidate will have hands-on expertise in building robust, scalable data pipelines, working with modern data platforms, and enabling data-driven decision-making across the organization.

You'll work closely with data scientists, analysts, and engineering teams to build and maintain efficient data infrastructure and tooling.

Responsibilities :

  • Design, develop, and maintain scalable ETL / ELT pipelines to support analytics and product use cases.
  • Collaborate with data analysts, scientists, and business stakeholders to gather requirements and translate them into data solutions.
  • Manage data integrations from various internal and external data sources.
  • Optimize data workflows for performance, cost-efficiency, and reliability.
  • Build and maintain data models and data warehouses using industry best practices.
  • Monitor, troubleshoot, and improve existing data pipelines.
  • Implement data quality frameworks and ensure data governance standards are followed.
  • Contribute to documentation, code reviews, and knowledge sharing within the team.

Requirements :

  • Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
  • 3-5 years of experience as a Data Engineer or in a similar data-focused role.
  • Strong command of SQL and proficiency in Python.
  • Good Engineering practices.
  • Experience with data pipeline orchestration tools such as Apache Airflow or equivalent.
  • Hands-on experience with cloud data platforms (AWS / GCP / Azure) and services such as S3 Redshift, BigQuery, or Azure Data Lake.
  • Experience in data warehousing concepts and tools like Snowflake, Redshift, and Databricks.
  • Familiarity with version control tools such as Git.
  • Strong analytical and communication skills.
  • Exposure to big data tools and frameworks such as Spark, Hadoop, or Kafka.
  • Experience with containerization (Docker / Kubernetes).
  • Familiarity with CI / CD pipelines and automation in data engineering.
  • Awareness of data security, privacy, and compliance principles
  • (ref : hirist.tech)

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