Data Integration Professionals

Key Responsibilities:

• Data Integration Development:

  • Design, implement, and maintain data integration solutions, including ETL processes, APIs, and data pipelines.
  • Integrate data from multiple internal and external sources, ensuring data consistency and accuracy.
  • Implement and support real-time and batch data integration workflows.

• ETL Process Design:

  • Develop and optimize Extract, Transform, Load (ETL) processes to efficiently move data between systems.
  • Ensure data quality and integrity during transformation and integration.

• Data Pipeline Management:

  • Create automated data pipelines for continuous data flow between systems.
  • Manage and monitor data workflows and resolve issues related to data integration and synchronization.

• Collaboration & Documentation:

  • Work closely with cross-functional teams (data analysts, data scientists, business analysts) to understand data requirements and provide solutions.
  • Develop clear and detailed technical documentation for data integration workflows and processes.

• Performance Optimization:

  • Optimize data integration processes for performance and scalability.
  • Troubleshoot and debug issues with data pipelines, resolving issues related to data transfer, transformation, and loading.

• Technology Stack:

  • Work with integration tools like

    Informatica

    ,

    Talend

    ,

    MuleSoft

    , or

    Apache Nifi

    .
  • Utilize database technologies like

    SQL

    ,

    NoSQL

    , and cloud platforms like

    AWS

    ,

    Azure

    , or

    Google Cloud

    for integration.
  • Implement data formats like

    JSON

    ,

    XML

    ,

    CSV

    , and

    Parquet

    .

Required Skills & Qualifications:

• Education:

  Bachelors degree in Computer Science, Information Technology, or a related field.

• Experience:

  Minimum [X] years of experience in data integration, ETL development, or data engineering.

• Technical Skills:

  • Strong proficiency in

    SQL

    ,

    Python

    , or other data-related programming languages.
  • Experience with ETL tools such as

    Informatica

    ,

    Talend

    ,

    Apache Nifi

    , or

    MuleSoft

    .
  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and services like

    AWS Glue

    ,

    Lambda

    ,

    S3

    ,

    Azure Data Factory

    , or

    Google Cloud Dataflow

    .
  • Knowledge of data formats (CSV, JSON, XML, Parquet) and APIs.