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Senior Data Engineer - ETL

Senior Data Engineer - ETL

Consulting FirmHyderabad
29 days ago
Job description

About the Role :

We are seeking a talented Data Engineer to join our team and play a pivotal role in transforming raw data into valuable insights. As a Data Engineer, you will design, develop, and maintain robust data pipelines and infrastructure to support our organization's analytics and decision-making :

  • Data Pipeline Development : Build and maintain scalable data pipelines to extract, transform, and load (ETL) data from various sources (e.g., databases, APIs, files) into data warehouses or data lakes.
  • Data Infrastructure : Design, implement, and manage data infrastructure components, including data warehouses, data lakes, and data marts.
  • Data Quality : Ensure data quality by implementing data validation, cleansing, and standardization processes.
  • Performance Optimization : Optimize data pipelines and infrastructure for performance and efficiency.
  • Collaboration : Collaborate with data analysts, scientists, and business stakeholders to understand their data needs and translate them into technical requirements.
  • Tool and Technology Selection : Evaluate and select appropriate data engineering tools and technologies (e.g., SQL, Python, Spark, Hadoop, cloud platforms).
  • Documentation : Create and maintain clear and comprehensive documentation for data pipelines, infrastructure, and

processes.

Skills :

  • Strong proficiency in SQL and at least one programming language (e.g., Python, Java).
  • Experience with data warehousing and data lake technologies (e.g., Snowflake, AWS Redshift, Databricks).
  • Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and cloud-based data services.
  • Understanding of data modeling and data architecture concepts.
  • Experience with ETL / ELT tools and frameworks.
  • Excellent problem-solving and analytical skills.
  • Ability to work independently and as part of a team.
  • Preferred Qualifications :

  • Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink).
  • Knowledge of machine learning and artificial intelligence concepts.
  • Experience with data visualization tools (e.g., Tableau, Power BI).
  • Certification in cloud platforms or data engineering.
  • (ref : hirist.tech)

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