Senior Data Engineer
2 weeks ago
Core responsibilities:
- Apply advanced knowledge of Data Engineering principles, methodologies and techniques to design and implement data loading and aggregation frameworks across broad areas of the organization.
- Gather and process raw, structured, semi-structured and unstructured data using batch and real-time data processing frameworks.
- Implement and optimize data solutions in enterprise data warehouses and big data repositories, focusing primarily on movement to the cloud.
- Drive new and enhanced capabilities to Enterprise Data Platform partners to meet the needs of product / engineering / business.
- Experience building enterprise systems especially using Databricks, Snowflake and platforms like Azure, AWS, GCP etc
- Leverage strong Python, Spark, SQL programming skills to construct robust pipelines for efficient data processing and analysis.
- Implement CI/CD pipelines for automating build, test, and deployment processes to accelerate the delivery of data solutions.
- Implement data modeling techniques to design and optimize data schemas, ensuring data integrity and performance.
- Drive continuous improvement initiatives to enhance performance, reliability, and scalability of our data infrastructure.
- Collaborate with data scientists, analysts, and other stakeholders to understand business requirements and translate them into technical solutions.
- Implement best practices for data governance, security, and compliance to ensure the integrity and confidentiality of our data assets.
- Proven experience (8+) in a data engineering role, with expertise in designing and building data pipelines, ETL processes, and data warehouses.
- Strong proficiency in SQL, Python and Spark programming languages.
- Strong experience with cloud platforms such as AWS, Azure, or GCP is a must.
- Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, and distributed computing frameworks.
- Knowledge of data lake and data warehouse solutions, including Databricks, Snowflake, Amazon Redshift, Google BigQuery, Azure Data Factory, Airflow etc.
- Experience in implementing CI/CD pipelines for automating build, test, and deployment processes.
- Solid understanding of data modeling concepts, data warehousing architectures, and data management best practices.
- Excellent communication and leadership skills, with the ability to effectively collaborate with cross-functional teams and drive consensus on technical decisions.
- Bachelor’s or master’s degree in computer science, Engineering, or a related field.
- Relevant certifications (e.g., Azure, Databricks, Snowflake) would be a plus.
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