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Data Platform Architect
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About Infostretch Corporation
Infostretch Corporation is a leading digital transformation company that specializes in accelerating business growth through innovative technology solutions. With a strong focus on delivering human-centric digital experiences, we help our clients outperform their competition through speed and innovation.
Job Title: Data Platform Engineer
We are seeking skilled Data Platform Engineers to join our expanding data engineering team. These positions are critical to our ongoing efforts to build and optimize our data infrastructure within the AWS ecosystem. You will play a key role in ensuring that our data pipelines are robust, scalable, and capable of supporting the needs of our analytics and data science teams.
Key Responsibilities:
- Develop and Maintain Data Pipelines: Design, develop, and maintain efficient data pipelines using Python and Airflow to automate the ingestion, transformation, and loading of data into Snowflake.
- Data Integration and API Development: Build and maintain integrations and APIs to facilitate data exchange between various systems and platforms.
- Data Warehouse Construction: Design, build, and populate data warehouses, ensuring data is structured optimally for querying and analysis.
- Data Quality and Transformation: Implement data quality checks, de-identification, and tokenization processes to maintain data integrity and privacy.
- Documentation: Prepare detailed data processing and design documentation, ensuring that all data engineering processes are well-documented and easily understandable by other team members.
Technical Requirements:
- Programming: Proficiency in Python, particularly with PySpark.
- AWS Services: Experience with AWS Glue, Airflow (MWAA), and other relevant AWS services.
- Data Warehousing: Hands-on experience with Snowflake or similar data warehousing solutions.
- ETL/ELT Processes: Strong understanding of data ingestion, transformation, and loading processes.
- Data Quality: Experience implementing data quality checks and data privacy techniques such as de-identification and tokenization.
Qualifications:
- Education: Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).
- Experience: 3-5 years of experience in data engineering or a related field.
- Communication: Strong written and verbal communication skills, with the ability to clearly articulate technical concepts to both technical and non-technical stakeholders.
