Data Engineer

AVEVA•San Leandro, CA

30d•$89,100 - $148,700•Hybrid

About The Position

We are seeking a skilled and motivated Data Engineer to join our Enterprise Data team. In this role, you will design, build, and optimize scalable data solutions that support business intelligence, analytics, and reporting initiatives across the organization. The ideal candidate will have experience developing modern data pipelines, data integration solutions, and data warehousing capabilities, with a strong focus on Microsoft Azure and Azure Synapse Analytics. This position partners closely with data analysts, business stakeholders, and technology teams to ensure data is reliable, accessible, and optimized for both operational and strategic decision-making.

Requirements

Bachelor's degree in Engineering, Computer Science, Information Systems, Mathematics, Statistics, or another STEM-related field.
Minimum 3 years of professional experience in Data Engineering, Data Warehousing, or a related field.
Experience designing and developing data pipelines and ETL/ELT processes.
Experience working with SQL and relational database technologies.
Experience supporting data integration, transformation, and data quality initiatives.
Knowledge of cloud-based data platforms and modern data architecture principles.

Nice To Haves

Experience with Microsoft Azure, including Azure Synapse Analytics, Azure Data Factory, Azure Data Lake, and related services.
Experience building enterprise-scale data warehouse and analytics solutions.
Proficiency in Python, Spark, or other data processing technologies.
Experience working with structured, semi-structured, and unstructured data sources.
Familiarity with data governance, security, and privacy best practices.
Strong analytical, problem-solving, and troubleshooting skills.
Excellent communication skills with the ability to work effectively across technical and business teams.

Responsibilities

Design, develop, and maintain scalable data pipelines using Azure Synapse Analytics and related Azure services.
Build and support data integration and ETL/ELT processes to ingest, transform, and consolidate data from multiple internal and external sources.
Develop and maintain data models and data warehousing solutions that support enterprise reporting and analytics needs.
Implement data cleansing, transformation, validation, and enrichment processes to ensure high-quality data.
Design and support solutions for both batch and real-time data processing requirements.
Monitor, troubleshoot, and optimize data pipeline performance, ensuring efficient processing and scalability.
Identify and resolve data quality, performance, and system reliability issues.
Collaborate with business partners, analysts, and technology teams to understand data requirements and deliver effective data solutions.
Ensure compliance with data governance, security, privacy, and regulatory requirements.
Create and maintain technical documentation, including data flows, ETL processes, data models, and operational procedures.
Support continuous improvement initiatives by identifying opportunities to automate and enhance data engineering processes.