Data Engineer - AT&T Alliance Mobile
About the Role
Alliance Mobile is seeking an experienced Data Engineer to build, operate, and continuously improve the data infrastructure supporting our applications, reporting, analytics, business operations, and strategic initiatives.
This is a hands-on engineering role with a strong emphasis on PostgreSQL, Python-based data engineering, and Azure Data Factory (ADF). Our environment includes production relational databases, operational systems, internal applications, third-party integrations, reporting platforms, cloud resources, and automated data pipelines.
Significant modernization work is already underway, and we are looking for an engineer who can quickly understand the existing environment, take ownership of technical initiatives, and continuously improve the systems that support the business.
The ideal candidate will have strong PostgreSQL and SQL expertise, solid experience building and maintaining production data pipelines with Python, and hands-on experience with Azure Data Factory. You should be comfortable determining whether a problem is best solved within PostgreSQL, through Python, with ADF, or through a combination of technologies.
Primary Mission
Build, operate, and continuously improve a reliable, scalable, and maintainable data platform supporting Alliance Mobile's applications, reporting, analytics, and operational needs.
Key Responsibilities
PostgreSQL & Database Engineering
• Design, maintain, and continuously improve PostgreSQL databases and supporting architecture.
• Work with schemas, tables, views, materialized views, indexes, functions, and other relational database structures.
• Write and optimize complex SQL and design efficient data models and access patterns.
• Diagnose query performance issues and monitor database performance, resource utilization, locking, and other operational concerns.
• Optimize indexing strategies and query execution and refactor inefficient or overly complex SQL and database logic.
• Support application developers and reporting teams with reliable and performant data structures.
• Help establish standards for database architecture, naming, performance, maintainability, and documentation.
• Evaluate whether processing belongs in the database, in Python, or another layer of the platform.
• Work with SQL Server and other relational systems as needed while maintaining PostgreSQL as a core part of the modern data environment.
Python Data Engineering
• Design, develop, and maintain production-grade data pipelines using Python.
• Build ingestion, transformation, validation, reconciliation, and automation processes.
• Integrate Python services and pipelines with PostgreSQL, APIs, files, third-party platforms, and cloud resources.
• Develop reusable Python utilities and frameworks for recurring data engineering needs.
• Build processes supporting batch, incremental, scheduled, and historical data processing.
• Implement appropriate error handling, retries, logging, validation, and recovery.
• Write maintainable, modular, and testable Python code and optimize processing for performance and reliability.
• Replace fragile or repetitive manual processes with automated solutions.
Python should be a core engineering skill in this role, not simply a scripting capability.
Azure Data Factory
• Design, build, maintain, and troubleshoot Azure Data Factory pipelines.
• Build orchestration workflows for ingestion, scheduling, transformation, and data movement.
• Implement dependencies, monitoring, alerting, failure handling, and recovery processes.
• Diagnose ADF failures, perform root-cause analysis, and improve existing workflows.
• Integrate ADF with PostgreSQL, SQL Server, Python processes, APIs, files, and cloud resources.
• Determine when ADF is the appropriate orchestration tool and when another solution provides a better long-term approach.
Strong ADF experience is important, but this role is not centered exclusively around ADF development.
ETL/ELT & Data Pipelines
• Design, build, maintain, and optimize scalable ETL and ELT pipelines.
• Develop automated ingestion processes for internal and external data sources, including APIs, databases, flat files, and scheduled extracts.
• Build solutions supporting incremental processing, historical backfills, reconciliation, and recovery.
• Develop reusable ingestion and transformation patterns rather than one-off workflows.
• Improve pipeline performance, reliability, and maintainability.
• Troubleshoot complex pipeline failures and implement durable solutions as business requirements evolve.
Data Architecture & Integration
• Develop and continuously improve Alliance Mobile's broader data architecture.
• Understand existing databases, pipelines, integrations, and reporting structures before making architectural changes.
• Design scalable relational data models and ingestion patterns and establish trusted source-of-truth datasets.
• Develop reusable patterns for onboarding new data sources and simplify duplicated or fragmented processes.
• Ensure data architecture supports internal applications, reporting, analytics, and future growth.
• Build integrations with APIs, databases, files, third-party systems, and cloud services.
• Handle authentication, pagination, schema changes, retries, and other production integration concerns.
• Work with software engineers to make operational and reporting data available efficiently.
• Participate in technical decision-making and long-term platform strategy.
Data Quality & Reconciliation
• Develop and maintain automated data validation and reconciliation processes.
• Identify missing, duplicated, inconsistent, incomplete, or unexpected data.
• Build PostgreSQL, SQL, and Python-based controls for critical datasets.
• Ensure consistency between source systems and downstream datasets.
• Develop mechanisms that surface data problems before they affect business users.
• Diagnose root causes and design controls that reduce recurring data quality problems.
Monitoring & Production Reliability
• Monitor databases, data pipelines, integrations, and scheduled processes.
• Establish meaningful logging, monitoring, observability, and alerting.
• Proactively identify failed loads, stale data, performance degradation, and other operational issues.
• Investigate production incidents, perform root-cause analysis, and implement preventative improvements.
• Improve visibility into pipeline health, runtimes, dependencies, and data freshness.
• Ensure critical data processes can recover safely from failures.
Automation & Continuous Improvement
• Identify repetitive, inefficient, or fragile processes and improve or automate them.
• Reduce manual intervention in critical data workflows.
• Continuously review databases, pipelines, and integrations for opportunities to improve performance and reliability.
• Reduce technical debt and improve documentation, testing, validation, and operational procedures.
End-to-End Project Ownership
• Own data engineering initiatives from requirements through production.
• Work with stakeholders to understand business problems and expected outcomes.
• Translate requirements into appropriate technical architecture and determine the right balance of PostgreSQL, Python, ADF, and cloud resources.
• Develop, test, validate, deploy, monitor, and support production solutions.
• Identify dependencies, risks, edge cases, and data quality concerns proactively.
• Take responsibility for successful production outcomes rather than simply completing assigned development tasks.
Required Qualifications
• 3+ years of professional Data Engineering or closely related engineering experience.
• Strong PostgreSQL and SQL experience, including database design, complex query development, performance tuning, and production database support.
• Strong Python development experience building production data pipelines, integrations, automation, and data processing workflows.
• Hands-on Azure Data Factory experience building, maintaining, monitoring, and troubleshooting production pipelines.
• Experience designing and maintaining ETL and ELT pipelines.
• Experience with relational data modeling and database architecture.
• Experience optimizing complex SQL queries and database workloads.
• Experience integrating APIs, databases, files, and third-party systems.
• Experience working with cloud-based resources and data services.
• Experience with incremental processing, historical backfills, validation, reconciliation, and pipeline recovery.
• Experience monitoring and troubleshooting production databases and data pipelines.
• Experience implementing logging, monitoring, and alerting and performing root-cause analysis.
• Experience carrying engineering projects from requirements through development, testing, deployment, and production support.
• Strong understanding of software engineering practices including Git, code review, testing, modular development, and maintainability.
• Strong problem-solving, analytical, communication, and collaboration skills.
• Ability to work independently, take ownership, quickly understand unfamiliar systems, and manage multiple technical priorities.
Ideal Candidate
You should be comfortable entering an existing production environment, understanding how it operates, identifying weaknesses or opportunities, and deciding whether the right solution is to optimize, refactor, extend, automate, or redesign a process.
This is not a reporting analyst role. This is not a dashboard developer role. This is not an ADF-only role. This is a full-time Data Engineering position centered around PostgreSQL, Python, and Azure Data Factory, with responsibility for continuously improving the data infrastructure Alliance Mobile depends on.
Employment Details
Position: Data Engineer
Employment Type: Full-Time, W-2
Location: Hybrid Remote / Troy, Michigan (as applicable)
Start Date: Immediate

Data Engineer

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