Job Title: Data Engineering Production Support Analyst (L2/L3 AWS ETL)
Charlotte, NC
Full Time
Overview / Summary
The role provides comprehensive L2/L3 production support for Data Engineering environments while working collaboratively with internal teams and stakeholders. Responsibilities include incident management, change management, data onboarding, source-to-target mapping, data quality management, impact assessment, agile delivery support, documentation, platform enablement, and operational support for data platforms.
Key Responsibilities
Provide incident management and change management support.
Perform triage and resolution of production incidents within SLA.
Support source-to-target mapping and data onboarding activities.
Partner with source system owners and business stakeholders to gather data requirements and translate them into actionable source-to-target mapping documents with documented transformation logic and acceptance criteria.
Collaborate with AI engineers, data modelers, and solution architects to ensure data pipelines support traditional analytics and high-volume data transformation requirements.
Design and review ETL architecture patterns on AWS, including Glue, Step Functions, S3, Redshift, and Athena.
Provide guidance on job orchestration, partitioning strategies, and historic storage approaches.
Write detailed JIRA stories covering business value, mapping changes, data onboarding steps, and expected platform impact.
Assess the impact of new data sources, product changes, and business enhancements on downstream screening and detection platforms, identifying risks before production deployment.
Hand off refined requirements to scrum teams and remain engaged during development and testing.
Identify and address data quality issues at the source in collaboration with data stewards and source owners.
Support data quality management and impact assessment activities.
Support data onboarding, lineage documentation, operational readiness, and platform enablement initiatives.
Leverage AI-assisted tooling, including code generation, automated testing, and intelligent data profiling, to improve delivery efficiency and platform effectiveness.
Perform daily monitoring of batch cycles, interfaces, and data loads.
Provide reconciliation support for positions, transactions, pricing, and accounting data.
Support user access and entitlement management.
Perform data validation and correction activities.
Coordinate with infrastructure, database, and upstream/downstream teams.
Implement minor enhancements and configuration updates.
Manage tickets through ServiceNow and Jira and communicate with stakeholders.
Participate in on-call and after-hours escalation support.
Required Qualifications
Hands-on SQL experience.
Strong ETL architecture knowledge.
Practical AWS experience with:
Glue
Lambda
S3
IAM
CloudWatch
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