Sr. Data Engineering Lead, Onsite, VP

About the Role

Key Responsibilities

• Design, develop, and maintain data pipelines in Azure for ingesting, transforming, and loading data from various sources into centralized Azure data lakes and Databricks Delta Lake. Ensure data quality and integrity throughout the process.
• Implement efficient ELT/ETL processes to ensure data quality, consistency, and reliability. Develop transformation processes to clean, aggregate, and enrich raw data, ensuring it is in the appropriate format for downstream analysis and consumption.
• Design and implement efficient data models and database schemas that support the storage and retrieval of structured and unstructured data. Optimize data storage and access for performance and scalability.
• Implement knowledge of modern data processing principles to streamline data import/transformation processes. Leverage modern data pipeline tools to reduce human attention during ETL process. Ensure the efficiency and reliability of data ingestion and processing.
• Work closely with cross-functional teams to understand data requirements and translate them into technical solutions.
• Monitor data pipelines, troubleshoot issues, and ensure data integrity and security.
• Implement data quality controls and validation processes to identify and rectify data anomalies, inconsistencies, and errors. Collaborate with stakeholders to define and enforce data governance standards and policies.
• Identify performance bottlenecks in data pipelines and database systems and optimize queries, data structures, and infrastructure configurations to improve overall system performance and scalability.
• Implement appropriate security measures to protect sensitive data and ensure compliance with data privacy regulations. Monitor and address data security vulnerabilities and risks.
• Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to understand data requirements and deliver effective data solutions. Document data engineering processes, data flows, and system configurations.
• Stay updated with the latest trends, tools, and technologies in the field of data engineering. Proactively identify opportunities to improve data engineering practices and contribute to the evolution of data infrastructure.
• Provide support to the development team with managing multiple instances of databases and servers, implementing complex queries with proper tuning, and managing data infrastructure in Azure (DataLake, DataWarehouse, and Synapse).

Requirements

• Hands-on experience with Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure SQL Database, etc.
• Strong experience in data engineering, including data pipeline development, ETL/ELT processes, and data modeling.
• Strong proficiency in SQL and experience with programming languages such as Scala or Java.
• In-depth knowledge of SQL and experience with relational and non-relational databases such as Snowflake, SQL Server, Oracle.
• Knowledge of data warehousing concepts, dimensional modeling, and best practices.
• Experience working in a multi-developer environment, using version control (i.e., Git).
• Excellent problem-solving skills and ability to work independently as well as part of a team.
• Effective communication skills, both written and oral.
• Experience of working in the financial industry and with agile development methodology.

Nice to Have

• Azure certifications such as Azure Data Engineer Associate or Azure Solutions Architect.
• Experience on Snowflake is a plus.

Qualifications

• Bachelor's Degree in a computer or IT related subject.
• 10+ years of overall IT industry experience.
• 8+ years of overall Big Data pipeline experience.
• 8+ years of experience as a Data Engineer, focusing on data solutions on Azure Databricks.
• 8+ years of experience with cloud-based development including Azure Services, Azure DevOps, Kubernetes, Docker.

Benefits & Perks

• Competitive and comprehensive benefits packages including medical care, insurance, and savings plans.
• Flexible Work Programs to match individual needs.
• Development programs and educational support to help reach full potential.
• Paid volunteer days, matching gift programs, and access to employee networks.