
ETL Data Architect
9 hours ago
The role of an ETL Data Integration Specialist is pivotal in our organization, requiring exceptional technical prowess and a sharp analytical mind.
This full-time position involves collaborating closely with clients to design, deploy, and manage data pipelines that integrate information from multiple sources.
Key responsibilities include:
- Designing, developing, and maintaining ETL pipelines using Informatica and other tools to process and transform large datasets effectively.
- Working extensively with SQL to query, optimize, and manage data across systems seamlessly.
- Implementing and optimizing data models following data warehousing concepts such as Star Schema, Snowflake Schema, Slowly Changing Dimensions, etc.
- Developing scalable data solutions and automation scripts using Python programming language.
- Leveraging GCP services such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, etc. for data ingestion, transformation, and storage.
- Collaborating with data analysts, data scientists, and business stakeholders to deliver reliable datasets and actionable insights.
- Monitoring and troubleshooting data pipelines to ensure optimal performance and data quality.
- Documenting data workflows, processes, and standards for future reference.
Requirements for this role include:
- 3-5 years of hands-on experience as a Data Engineer or in a similar position.
- Strong proficiency in SQL (query optimization, stored procedures, performance tuning).
- Solid experience with ETL development using Informatica and strong knowledge of data warehousing concepts.
- Proficient in Python programming for data processing and automation.
- Practical experience working with GCP services, especially BigQuery.
- Understanding of data governance, data quality, and performance best practices.
- Strong problem-solving skills and the ability to work collaboratively in a team environment.
Benefits include:
- Exposure to MLOps pipelines or integration with machine learning models.
- Knowledge of other cloud platforms (AWS/Azure) and their data engineering services.
- Experience with CI/CD tools and containerization (Docker/Kubernetes).
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