Design and implement scalable ETL and ELT processes using GCP services to ensure high data availability and performance. Manage data workflows with Apache Airflow and maintain data warehousing solutions across various platforms.
Senior ETL / Data Engineer
Experience: 5-10 Years
Location: Remote
Summary
We are seeking an experienced Senior ETL and Data Engineer to architect, build, and optimize robust data pipelines within a cloud-native environment. This pivotal role is responsible for designing scalable data integration solutions that ensure high availability, accuracy, and performance across our data infrastructure. The ideal candidate will bridge the gap between complex data sources and actionable insights, leveraging advanced cloud technologies and automation frameworks to drive data reliability and efficiency for the organization.
Responsibilities
Design and implement scalable ETL and ELT processes utilizing GCP services such as BigQuery, Cloud Dataflow, and Cloud Data Fusion.
Manage and orchestrate data workflows using Cloud Composer (Apache Airflow) to ensure seamless data movement and processing.
Develop and maintain data warehousing solutions across diverse platforms including Snowflake, Oracle, Teradata, and various SQL databases.
Write efficient, high-performance code in Java and Python to handle complex data transformations and logic.
Construct advanced SQL queries involving window functions, CTEs, and complex joins to extract and manipulate data.
Establish and enforce rigorous testing protocols, including source-to-target reconciliation, schema validation, and regression testing.
Integrate data pipelines into CI/CD workflows using Jenkins, Git, and GCP Cloud Build to streamline deployment and version control.
Collaborate within an Agile environment using Jira and Confluence to track progress, manage defects, and document technical specifications.
Utilize tools like Informatica PowerCenter and Talend for enterprise-level data integration tasks.
Requirements
Experience: 5 to 10 years of professional experience in data engineering, ETL testing, or related fields.
Cloud Expertise: Proven proficiency with Google Cloud Platform (GCP) services, specifically BigQuery, Cloud Storage, and Cloud Composer.
Database Skills: Strong command of relational and NoSQL databases, including PostgreSQL, MySQL, Cloud SQL, Cloud Spanner, Oracle, and Snowflake.
Programming: Advanced skills in Java (JDBC, Apache Beam SDK) and Python (Pandas, PyTest).
SQL Mastery: Expert-level knowledge of SQL, including complex joins, window functions, and PL/SQL.
Testing & QA: Hands-on experience with testing frameworks like TestNG, JUnit, and BDD Cucumber, along with data-driven testing methodologies.
DevOps & Tools: Familiarity with CI/CD pipelines, Git, GitHub, Maven, and defect tracking systems like Jira and HP ALM.
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