Data Engineer
1 month ago
Key Responsibilities:
● Design, develop, and optimize complex SQL queries to transform and extract insights from large datasets.
● Build and maintain scalable ETL pipelines using Python to ingest, process, and load data from various sources into our data lake and data warehouse.
● Implement best practices for data governance, data quality, and data security.
● Work with massively parallel processing (MPP) data warehouses like BigQuery, Redshift, and Snowflake to manage and analyze large datasets efficiently.
● Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and provide robust data solutions.
● Set up and build data sources for dashboards to minimize repetitive ad-hoc data requests.
● Monitor and troubleshoot data pipelines to ensure reliability and performance.
● Document data workflows, ETL processes, and system architectures.
● Stay current with the latest data engineering technologies and methodologies to continuously improve our data infrastructure.
● Work within AWS or GCP environments; experience with multi-cloud environments is preferred.
● Develop and maintain data models using dbt (data build tool) to ensure consistency, quality, and efficiency in data transformations.
● Evaluate proof of concepts with new data solutions to improve existing architecture.
Required Qualifications :
● 1 - 2 years of relevant Data Engineering experience.
● Proven experience in writing and optimizing complex SQL queries.
● Strong proficiency in Python for ETL pipeline development.
● Experience with docker containerization and Kubernetes for pipeline orchestration.
● Experience with any MPP data warehouses such as BigQuery, Redshift, and Snowflake
● Experience working with cloud platforms such as AWS and GCP; multi-cloud experience is a plus.
● Experience with data flow orchestration tools like Apache Airflow or Dagster.
● Experience with data modeling and transformation using dbt (data build tool).
● Solid understanding of data warehousing concepts, data modeling, and data architecture.
● Knowledge of data governance, data quality, and data security best practices.
● Excellent problem-solving skills and attention to detail.
● Strong communication and collaboration skills, with the ability to work effectively in a team environment.
● Experience with data catalogs and data lineage tools would be a plus
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