Responsibilities:* Design, build, and maintain robust and scalable data pipelines that ingest, process, and store data from various sources.* Develop and implement ETL (Extract, Transform, Load) processes for data integration and warehousing.* Ensure data quality and integrity through data validation, cleansing, and monitoring.* Collaborate with data scientists, analysts, and other stakeholders to understand data needs and provide data solutions.* Optimize data pipelines for performance and cost efficiency.* Research and evaluate new data technologies and tools to improve our data infrastructure.* Document data processes and maintain data dictionaries.* Troubleshoot and resolve data-related issues.* Stay up-to-date with the latest trends and best practices in data engineering.* Contribute to the development of data governance policies and procedures. * Technical Skills: * Programming Languages: Proficiency in at least one programming language such as Python, Java, Scala, or Go. * Databases: Experience with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra). * Big Data Technologies: Experience with Azure Databricks, Snowflake, Hadoop, Spark, Hive, Kafka, or other big data processing frameworks. * Cloud Platforms: Experience with cloud computing platforms such as AWS, Azure, or GCP (Azure is preferred). * ETL Tools: Experience with ETL tools such as Informatica, Talend, or Apache Airflow. * Data Warehousing: Understanding of data warehousing concepts and techniques. * Data Modeling: Experience with data modeling and schema design. * SQL: Strong SQL skills. * Linux/Unix: Familiarity with Linux/Unix operating systems. * Version Control: Experience with Git or other version control systems.
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