Senior Data Architect

4 days ago


Hyderabad, Telangana, India Saras Analytics Full time

About Saras Analytics

We are a leading provider of data analytics solutions, helping enterprises and brands make informed decisions to drive business growth. Our expertise spans the entire data lifecycle, from extraction and transformation to visualization and analysis. We have developed a suite of products and services that leverage industry-leading technology to deliver value to our customers.

Our Vision

We strive to be an employee-first company, valuing talent and encouraging innovation and collaboration. We believe in creating a culture that fosters growth, learning, and excellence, both for our employees and our customers.

The Role

We are seeking an experienced Lead Data Engineer to join our team. The successful candidate will have a strong background in programming, cloud platforms, and data warehousing technologies. As a key leader in our data engineering team, you will play a critical role in designing, implementing, and optimizing data pipelines, leveraging your expertise in programming, cloud platforms, and modern data warehousing solutions.

  • Data Pipeline Architecture: Design and implement scalable and efficient data pipelines, ensuring optimal performance and reliability.
  • Programming and Scripting: Utilize strong programming skills, particularly in languages like Python, for developing robust and maintainable data engineering solutions.
  • Cloud Platform Expertise: Apply extensive experience with cloud platforms (e.g., AWS, Azure, Google Cloud) to design, deploy, and optimize data engineering solutions in a cloud environment.
  • BigQuery/Snowflake Knowledge: Demonstrate deep understanding and hands-on experience with BigQuery/Snowflake for efficient data storage, processing, and analysis.
  • ETL Processes: Lead the development of Extract, Transform, Load (ETL) processes, ensuring seamless integration of data from various sources into the data warehouse.
  • Data Modeling and Optimization: Design and implement effective data models to support ETL processes and ensure data integrity and efficiency.
  • Collaboration and Leadership: Collaborate with cross-functional teams, providing technical leadership and guidance to junior data engineers.
  • Quality Assurance: Implement comprehensive data quality checks and validation processes to ensure the accuracy and completeness of data.
  • Documentation: Create and maintain detailed documentation for data engineering processes, data models, and cloud configurations.


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