Cyber Managed Services - Data Engineer - Senior

EY•Charlotte, NC

2d•$77,500 - $160,500

About The Position

The Senior Data Engineer will design, develop, test, deploy, and support secure, scalable data solutions that consolidate identity and access data from enterprise source systems into a centralized operational data store. The platform supports access visibility, operational reporting, risk analysis, remediation, automation, and decision-making. The engineer contributes throughout the data-delivery lifecycle, including source-system discovery, data analysis, dimensional and relational modeling, ETL development, pipeline orchestration, data-quality validation, performance tuning, release automation, and production support. The role requires recent hands-on Microsoft SQL Server or Azure SQL engineering experience and the ability to deliver independently within an integrated Agile product team. The position is based in Dallas, Alpharetta, Charlotte, Jacksonville, or San Antonio. The salary range for these and other US locations not specifically listed is $77,500 to $140,900. Individual salaries depend on factors including education, experience, knowledge, skills, and geography.

Requirements

Bachelor’s degree in computer science, data engineering, information technology, information systems, or a related field, or equivalent practical experience.
Approximately 6–9 years of enterprise data-engineering, database-development, or related experience.
At least five years of strong SQL development experience, including complex queries, stored procedures, performance tuning, indexing, and relational database design.
Recent hands-on development experience within the last three years using Microsoft SQL Server, Azure SQL Database, or Azure SQL Managed Instance.
Strong understanding of relational and dimensional data modeling, normalization, data warehousing, operational data stores, fact and dimension structures, and slowly changing dimensions.
Experience designing, developing, and supporting ETL pipelines and data-ingestion solutions for high-volume, multi-source enterprise data.
Experience with SnapLogic or a comparable enterprise integration platform.
Proficiency in one or more supporting languages or tools such as Python, PowerShell, Unix shell scripting, or PL/SQL.
Experience with Microsoft Azure data services and cloud-based database solutions.
Experience implementing data-quality checks, source-to-target reconciliation, error handling, logging, monitoring, and operational support processes.
Experience with Git-based source control, CI/CD pipelines, automated deployment, and tools such as Jenkins and Docker.
Experience testing database changes, transformations, and end-to-end ingestion flows across multiple environments.
Familiarity with Agile delivery practices and tools such as Jira and Confluence.
Strong analytical, problem-solving, documentation, communication, and stakeholder-management skills.
Ability to work independently, review existing solutions, identify gaps, and deliver production-ready enhancements with limited ramp-up time.

Nice To Haves

Experience delivering data solutions for identity and access management, identity governance, privileged access management, cybersecurity, or technology-risk use cases.
Familiarity with IAM data domains such as identities, accounts, entitlements, applications, credentials, privileged access, certifications, and lifecycle events.
Experience building centralized operational data stores that support reporting, risk analysis, remediation, automation, and audit evidence.
Hands-on experience with SnapLogic, including API, database, file, and cloud integration pipelines.
Experience integrating Microsoft Graph, REST APIs, LDAP or Active Directory data, and structured or semi-structured file sources.
Experience with Azure Data Factory, Azure Databricks, PySpark, Informatica, Snowflake, Oracle, PostgreSQL, or comparable data technologies.
Familiarity with Microsoft SQL Server, PostgreSQL variants such as YugabyteDB or CockroachDB, Oracle, DB2, and cloud-hosted database inventory or audit data.
Experience creating reporting-ready datasets for Power BI, Tableau, or comparable analytics platforms.
Experience with graph databases or analytics platforms such as Neo4j.
Familiarity with data lineage, metadata management, control reporting, and enterprise data-governance practices.
Experience in a regulated financial-services environment and knowledge of secure software development, change management, and production-readiness controls.
Relevant Microsoft Azure, database, data-engineering, or cybersecurity certifications.

Responsibilities

Design, develop, test, and maintain data pipelines and database solutions for the IAM Operational Data Store and related reporting applications.
Analyze source-system data and translate business, reporting, risk, and control requirements into conceptual, logical, and physical data models.
Develop and optimize Microsoft SQL Server and Azure SQL objects, including complex queries, stored procedures, views, functions, indexes, partitions, and transformation logic.
Build repeatable ETL and ingestion patterns for identity, account, entitlement, credential, inventory, activity, certification, lifecycle, and control-related data.
Develop and maintain SnapLogic pipelines and scripts for data extraction, transformation, validation, reconciliation, and loading.
Integrate cloud and on-premises data sources using databases, APIs, Microsoft Graph, flat files, and other enterprise integration patterns.
Create prepared-layer tables, source-to-target mappings, reusable transformation components, and reporting-ready datasets.
Implement data-quality checks, reconciliation routines, health indicators, exception handling, logging, retry logic, and operational monitoring.
Tune database queries, pipelines, and data models to improve performance, scalability, reliability, and cost effectiveness.
Protect sensitive identity and access data using secure database design, least-privilege access, secrets management, encryption, and data-handling practices.
Build and maintain CI/CD pipelines and deployment processes for controlled promotion across development, quality-assurance, pre-production, and production environments.
Perform unit, integration, regression, data-quality, and production-validation testing for ingestion pipelines and database changes.
Troubleshoot data, application, pipeline, database, API, and deployment issues using logs, query plans, monitoring tools, and reconciliation evidence.
Collaborate with analysts, product owners, architects, data-source owners, reporting engineers, security teams, and business stakeholders to define and deliver end-to-end data solutions.
Participate in Agile ceremonies, backlog refinement, sprint planning, demonstrations, code and design reviews, release readiness, and continuous-improvement activities.
Create and maintain technical designs, data models, lineage documentation, implementation procedures, test evidence, operational runbooks, and support materials.