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Lead Data Engineer @ Atyeti

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 Lead Data Engineer

Job Description

Role & responsibilities

  • Develop and Maintain Data Pipelines: Design, develop, and manage scalable ETL pipelines to process large datasets using PySpark, Databricks, and other big data technologies.
  • Data Integration and Transformation: Work with various structured and unstructured data sources to build efficient data workflows and integrate them into a central data warehouse.
  • Collaborate with Data Scientists & Analysts: Work closely with the data science and business intelligence teams to ensure the right data is available for advanced analytics, machine learning, and reporting.
  • Optimize Performance: Optimize and tune data pipelines and ETL processes to improve data throughput and reduce latency, ensuring timely delivery of high-quality data.
  • Automation and Monitoring: Implement automated workflows and monitoring tools to ensure data pipelines are running smoothly, and issues are proactively addressed.
  • Ensure Data Quality: Build and maintain validation mechanisms to ensure the accuracy and consistency of the data.
  • Data Storage and Access: Work with data storage solutions (e.g., Azure, AWS, Google Cloud) to ensure effective data storage and fast access for downstream users.
  • Documentation and Reporting: Maintain proper documentation for all data processes and architectures to facilitate easier understanding and onboarding of new team members.

Skills and Qualifications:

  • Experience: 5+ years of experience as a Data Engineer or similar role, with hands-on experience in designing, building, and maintaining ETL pipelines.
  • Technologies:
    • Proficient in PySpark for large-scale data processing.
    • Strong programming experience in Python, particularly for data engineering tasks.
    • Experience working with Databricks for big data processing and collaboration.
    • Hands-on experience with data storage solutions (e.g., AWS S3, Azure Data Lake, or Google Cloud Storage).
    • Solid understanding of ETL concepts, tools, and best practices.
    • Familiarity with SQL for querying and manipulating data in relational databases.
    • Experience working with data orchestration tools such as Apache Airflow or Luigi is a plus.
  • Data Modeling & Warehousing:
    • Experience with data warehousing concepts and technologies (e.g., Redshift, Snowflake, or BigQuery).
    • Knowledge of data modeling, data transformations, and dimensional modeling.
  • Soft Skills:
    • Strong analytical and problem-solving skills.
    • Excellent communication skills, capable of explaining complex data processes to non-technical stakeholders.
    • Ability to work in a fast-paced, collaborative environment and manage multiple priorities.

Preferred Qualifications:

  • Bachelor's or Masters degree in Computer Science, Engineering, or a related field.
  • Certification or experience with cloud platforms like AWS, Azure, or Google Cloud.
  • Experience in Apache Kafka or other stream-processing technologies.

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Engineering - Software & QA
Role Category: Software Development
Role: Data Engineer
Employement Type: Full time

Contact Details:

Company: Atyeti
Location(s): Pune

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Keyskills:   Pyspark Spark Data Bricks Python azure

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