Senior Data Engineer

Fidelity • Westlake, TX

22h • Hybrid

About The Position

Position Description : Builds and optimizes clean, well-documented, and reusable data transformations in SQL, Python, and Cloud-based platforms to enable self-service analytics and data science. Supports dashboards and visualization platforms (Power BI and Tableau) by preparing optimized datasets and ensuring performance at scale. Works on data consulting projects using technical and analytical strengths and skills. Identifies , analyzes, and proposes solutions to support consulting projects and provide support to clients directly, using service category databases, data warehouses, and other technical applications (Python, SQL, and Snowflake). Designs, develops, and maintains robust, scalable data pipelines and analytics-ready data models to support business intelligence, reporting and advanced analytics use cases .

Requirements

• Bachelor’s degree in Analytics, Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Senior Data Engineer (or closely related occupation) building and supporting scalable data warehousing and reporting platforms in hybrid Cloud environments (Snowflake, SQL, Python, and Power BI).
• Or, alternatively, Master’s degree in Analytics, Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and one (1) year of experience as a Senior Data Engineer (or closely related occupation) building and supporting scalable data warehousing and reporting platforms in hybrid Cloud environments (Snowflake, SQL, Python, and Power BI).
• Demonstrated Expertise (“DE”) implementing end-to-end Extract, Transform, Load (ETL) workflows using Amazon Web Services (AWS) services (Glue, Simple Storage Service (S3), DynamoDB, Elastic Compute Cloud (EC2), and Jenkins); and building data ingestion pipelines with SQL, Python and Informatica to process structured and unstructured data across distributed Cloud-native environments.
• DE developing migration and reporting solutions using Azure services (Data Factory, Logic apps, and Blob Storage), SQL, C#/.NET, and dashboarding tool (Power BI); and streamlining data availability and insight delivery.
• DE architecting automated data transformation frameworks using Python, Java, and advanced SQL procedures; and optimizing performance and enabling regulatory and analytical data outputs for enterprise consumption, using Python, Java and SQL.
• DE building and maintaining observability and monitoring frameworks, using Datadog, Azure monitor, and CloudWatch; and performing database-level auditing to validate data quality, track job performance, and ensure compliance with Service Level Agreements (SLAs) across production pipelines, using Datadog, Azure monitor, and CloudWatch .

Responsibilities

• Architects and maintains enterprise data marts, semantic layers, and curated datasets, ensuring data consistency and accuracy for analytics consumption.
• Implements data quality checks, validation rules, and lineage tracking to ensure trust in critical business metrics and reports.
• Develops and automates data ingestion, enrichment, and aggregation workflows across structured and unstructured data sources.
• Creates and maintains technical documentation, data dictionaries, and data mapping artifacts to support transparency and knowledge sharing across teams.
• Applies data modelling techniques, statistical methods, and advanced tools to enable reporting, forecasting, and actionable insights.
• Provides performance and operational insights.
• Works with product owners, technical leads, and architects to influence technical platform improvements .

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees