Data Engineer (SQL Server / SSIS / AWS

Ares Holdings, LLC
Memphis, United States of America
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote
Memphis, United States of America

Tech stack

.NET
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Cloud Database
Code Review
Databases
Data Validation
Information Engineering
Data Governance
Data Integration
Data Integrity
ETL
Data Transformation
Data Systems
Data Warehousing
Python
Microsoft SQL Server
Operational Databases
Performance Tuning
Query Optimization
Release Management
Cloud Services
SQL Databases
SQL Server Integration Services
Software Technical Review
Enterprise Data Management
Data Processing
Cloud Platform System
Data Ingestion
Data Build Tool (dbt)
Database Performance
Change Data Capture
GIT
Data Lake
Data Lineage
Bitbucket
Data Management
Api Design
Cloudwatch
Software Version Control
Data Pipelines

Job description

We are seeking an experienced Senior Data Engineer to design, build, and support scalable data integration solutions that power enterprise analytics and business intelligence initiatives. This role is ideal for someone who enjoys solving complex data engineering challenges, optimizing large-scale data pipelines, and collaborating across technical teams to deliver reliable, high-quality data solutions.

The ideal candidate has deep expertise in SQL Server, SSIS, modern ETL/ELT development, cloud-based data platforms, and performance optimization, along with experience building resilient data ingestion pipelines in enterprise environments., * Design, develop, and maintain enterprise data ingestion pipelines supporting full data loads, incremental processing, and change data capture.

  • Build and support SQL Server-based and API-driven data integration solutions.
  • Develop and maintain ETL/ELT workflows that move data into centralized data platforms.
  • Optimize SQL queries, indexes, and database performance to ensure scalable, efficient processing.
  • Troubleshoot production issues involving data quality, pipeline failures, and performance bottlenecks.
  • Design monitoring, alerting, and validation processes to improve pipeline reliability and data integrity.
  • Participate in architectural discussions focused on scalability, performance, reliability, and operational efficiency.
  • Collaborate with architects, application teams, and data engineering partners to support end-to-end data movement.
  • Participate in code reviews and technical design reviews while promoting engineering best practices.
  • Create and maintain technical documentation, process flows, and implementation diagrams.

Requirements

  • Strong experience designing and supporting enterprise data ingestion and synchronization pipelines.
  • Advanced SQL Server expertise, including:
  • Query optimization
  • Performance tuning
  • Index design
  • Blocking and locking analysis
  • Troubleshooting complex database issues
  • Hands-on experience developing SSIS packages and data movement workflows.
  • Experience building and supporting ETL/ELT pipelines within data warehouse or data lake environments.
  • Experience with cloud-based data engineering solutions using AWS services such as:
  • S3
  • Lambda
  • Glue
  • Athena
  • CloudWatch
  • CloudTrail
  • Experience designing cloud-native data pipelines.
  • Experience with .NET-based data processing solutions.
  • Working knowledge of Python for data engineering tasks.
  • Experience implementing data validation, reconciliation, and data quality processes.
  • Experience designing monitoring, observability, and alerting for production data pipelines.
  • Experience using Git, Bitbucket, or similar source control and release management tools.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Excellent communication skills with the ability to collaborate across technical teams.

Preferred Qualifications

  • Experience using DBT (Data Build Tool) for modern data transformation.
  • Experience with connector-based data integration platforms such as CData or similar technologies.
  • Familiarity with AWS architectural best practices and cloud design principles.
  • Knowledge of data governance, data lineage, and data ownership practices.
  • Experience contributing to technical architecture decisions and mentoring other engineers.
  • Experience working within enterprise-scale data engineering environments.

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