Hamilton Lane is a recognized leader in providing Private Markets Solutions to clients across the globe. They are seeking a talented ETL Data Engineer to design, develop, and maintain ETL data integration processes, ensuring the accuracy and availability of data for analytical needs.
Responsibilities:
- ETL Data Engineering: Develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks, and/or Azure Synapse Analytics Pipelines, to ensure efficient data extractions, transformation, and loading
- Data Warehousing: Apply your expertise in data warehousing, understanding star schemas, facts, and dimensions, to design and build effective data storage structures in a Massively Parallel Processing (MPP) SWL Pool
- Data Source Expertise: Extract data from various sources, including REST APIs, SWL database tables, and CSV files
- Azure Synapse Analytics Expertise: Utilize your deep knowledge of Azure Synapse Analytics to design and optimize data notebooks/pipelines for scalability and performance
- Data Fabric Concepts: Contribute to the implementation and understanding of other Data Fabric concepts, such as data lakes, lakehouses, delta lakes, and data cataloging, to enhance data management capabilities
- Data Modeling: Collaborate with data architects to create data models and schemas that align with business requirements
- Data Quality: Implement data quality checks and validation processes to maintain data accuracy and consistency
- Performance Tuning: Identify and resolve performance bottlenecks and optimize ETL data notebooks/pipelines to meet SLAs
- Monitoring and Troubleshooting: Monitoring ETL jobs, diagnose issues, and implement solutions to ensure data pipeline reliability
- Documentation: Maintain comprehensive documentation of ETL data engineering processes, data flows, and data transformations
- Collaboration: Work closely with cross-functional teams to understand data requirements and provide support for data-related initiatives
- Security and Compliance: Ensure data security and compliance with data governance and privacy standards
Requirements:
- Bachelor's degree in Computer Science, Information Technology, or a related field; or equivalent work experience, with certifications related to data engineering or data science (e.g. Azure Data Engineer) being a plus
- Proven experience in ETL data engineering with significant expertise in using Python (PySpark) to perform data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files
- Proficiency in using Azure Synapse Analytics resources including Notebooks, Pipelines, Linked Services, and Azure Key Vault
- Demonstrated ability to write complex SQL queries, optimize query performance, and work with both SparkSQL and MS SQL to effectively extract, transform, and load data
- Knowledge of data integration best practices and tools
- Experience with version control systems, such as Git (Azure DevOps)
- Strong problem-solving and analytical skills, with a keen attention to detail
- Excellent communication skills, both verbal and written, with the ability to work collaboratively in a team environment with shifting priorities
- Familiarity with big data technologies, machine learning, and data analysis preferred
- Experience with data visualization tools (e.g. Power BI, Tableau) and Agile Methodologies a plus