Senior Data Engineering Lead, VP

Role Overview

• 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
• Integrate data from diverse sources to provide a unified view of information
• 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
• Document data engineering processes, data flows, and system configurations
• Stay updated with the latest trends, tools, and technologies in the field of data engineering
• Provide support to the development team with managing multiple instances of databases and servers, implementing complex queries with proper tuning, provide input to design impacting data, manage data infrastructure in Azure (DataLake, DataWarehouse and Synapse)

Requirements

• Bachelor's Degree level qualification in a computer or IT related subject
• 10+ years of overall IT industry experience
• 8+ years of overall Bigdata data pipeline experience
• 8+ years of experience as a Data Engineer, with a focus on designing and implementing data solutions on the Azure Databricks
• 8+ years of experience on cloud-based development including Azure Services, Azure Devops, Kubernetes, Docker
• Strong 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, SQLServer, 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
• Azure certifications such as Azure Data Engineer Associate or Azure Solutions Architect is a plus

Tech Stack

• Azure
• Cloud
• Docker
• ETL
• Java
• Kubernetes
• Oracle
• Scala
• SQL

Benefits

• health insurance including basic life, medical, dental, vision, long-term disability, and other optional additional coverages
• retirement savings plan (401K) with company match
• paid-time off including vacation, sick leave, short term disability, and family care responsibilities
• access to our Employee Assistance Program
• incentive compensation including eligibility for annual performance-based awards