Data Engineer
Robert Half Technology
Description
Design, develop, and maintain scalable ETL (Extract, Transform, Load) pipelines to process large volumes of structured and unstructured data.
Build and optimize data models, data lakes, and data warehouses for efficient storage and retrieval.
Develop and maintain real-time and batch data processing systems.
Ensure data integrity, security, and compliance with industry best practices and regulatory requirements.
Collaborate with data scientists and analysts to provide clean and structured data for analysis and machine learning applications.
Optimize database performance and troubleshoot data-related issues.
Work with cloud-based or on-premises data platforms such as AWS, Azure, or Google Cloud.
Automate data workflows using orchestration tools like Apache Airflow, Prefect, or similar frameworks.
Implement and manage data governance policies, including data lineage and quality control measures.
Stay up to date with emerging data engineering trends, tools, and best practices.
Requirements
Proficiency in SQL and experience with relational databases (PostgreSQL, MySQL, SQL Server, etc.).
Strong programming skills in Python, Java, Scala, or another relevant language.
Firsthand experience with ETL tools and frameworks (Apache Airflow, Talend, dbt, etc.).
Experience with big data technologies such as Hadoop, Spark, or Kafka.
Familiarity with cloud platforms (AWS, Azure, GCP) and their data services (Redshift, BigQuery, Snowflake, etc.).
Knowledge of data warehousing concepts, data modeling, and schema design.
Strong problem-solving skills and ability to work in a fast-paced environment.
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