Sr Data Engineer Data & Intelligence (T Mobile Finance)

TekWissen LLC

Frisco, TX

JOB DETAILS
SALARY
$43.43–$43.43
SKILLS
AWS Lambda, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Analysis Skills, Apache Kafka, Best Practices, Billing, Candidate Pipeline, Centers for Disease Control and Prevention (CDC), Cisco Unity, Cloud Computing, Code Reviews, Continuous Deployment/Delivery, Continuous Integration, Data Analysis, Data Management, Data Modeling, Data Processing, Data Quality, Database Extract Transform and Load (ETL), DevOps, Diversity, Error Handling, Finance, Financial Reporting, Git, GitHub, Information Technology & Information Systems, Instrumentation, Integration Testing, Machine Tool, Mentoring, Metrics, Microsoft Windows Azure, On Call, Operational Expenditure (OPEX), Performance Tuning/Optimization, Production Specifications, Production Support, Production Systems, Pytest, Python Programming/Scripting Language, Reconciliation, Requirements Management, SQL (Structured Query Language), Scala Programming Language, Scalable System Development, Scripting (Scripting Languages), Service Level Agreement (SLA), Snowflake Schema, Star Schema, Telecommunications Industry, Unit Test, Unix Shell Programming, Use Cases, Workforce Management
LOCATION
Frisco, TX
POSTED
1 day ago
Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation, information technology and services
Position: Sr Data Engineer Data & Intelligence (T Mobile Finance)
Location: Frisco, TX
Duration: 7 Months
Job Type: Temporary Assignment
Work Type: Hybrid
Job Description:
Job Summary:
  • We are seeking a Senior Data Engineer to design, build, and operate highly scalable batch and streaming data pipelines supporting T Mobile's Finance and Intelligence platforms.
  • This role requires deep expertise in modern cloud data stacks (Snowflake, Databricks, dbt), strong SQL/Python skills, and solid understanding of finance data domains including billing, revenue, GL, and OPEX.
  • The ideal candidate owns complex pipelines end to end, mentors junior engineers, and helps drive platform standards and best practices.
Key Responsibilities:
Data Pipeline Development:
  • Design and build scalable, reliable ELT/ETL pipelines for finance data (billing, revenue, GL, OPEX).
  • Implement batch and incremental ingestion patterns (full load, CDC, watermark-based).
  • Build idempotent, rerunnable pipelines with robust error handling, retry logic, and dead-letter queue patterns.
Platform & Tooling:
  • Develop and optimize pipelines using Snowflake (Snowpipe, Streams, Tasks, Dynamic Tables, performance tuning).
  • Build data processing workflows in Databricks (PySpark, Delta Live Tables, Unity Catalog, job clusters).
  • Create and maintain dbt models, tests, snapshots, macros, and packages with CI integration.
  • Orchestrate data workflows using Airflow or Azure Data Factory (DAG design, dependencies, scheduling, alerts).
Cloud Infrastructure:
  • Work within Azure (ADLS Gen2, Event Hub, ADF, Azure Functions, Key Vault) and/or AWS (S3, Glue, Lambda, Secrets Manager).
  • Apply Infrastructure as Code fundamentals (Terraform, Bicep) for pipeline and resource provisioning.
  • Apply cloud cost awareness including compute sizing, partitioning strategies, and storage optimization.
Languages & Frameworks:
  • Write advanced SQL (CTEs, window functions, query tuning, execution plan analysis).
  • Develop in Python (pandas, PySpark, requests, pytest, logging).
  • Read and modify existing Scala/Spark jobs as needed.
  • Use shell scripting for automation and operational tasks.
Streaming & Real Time Processing:
  • Build near real time pipelines using Apache Kafka / Azure Event Hub.
  • Implement Spark Structured Streaming with stateful aggregations, watermarking, and checkpointing.
  • Support finance use cases such as revenue reconciliation and fraud signal feeds.
Data Quality & Testing:
  • Implement unit and integration testing for pipelines (pytest, dbt tests).
  • Create data quality checks (row counts, nulls, duplicates, referential integrity).
  • Use Great Expectations or custom frameworks for validation.
  • Monitor SLAs for pipeline latency and data freshness with alerting.
Data Modeling Support:
  • Implement architected schemas (star, snowflake, data vault).
  • Manage Slowly Changing Dimensions (SCD Type 1 & 2) for finance entities.
  • Define partitioning and clustering strategies for large-scale finance tables.
  • Support semantic layer definitions (metrics and dimensions).
DevOps & Engineering Practices:
  • Participate in CI/CD for data pipelines using GitHub Actions or Azure DevOps.
  • Follow Git branching strategies (trunk-based, feature branches).
  • Perform code reviews and enforce engineering standards.
  • Support environment promotion patterns (dev QA prod).
Security & Governance:
  • Implement RBAC and row/column-level security in Snowflake and Databricks.
  • Ensure PII and CPNI handling per T Mobile TISS 310 policy.
  • Manage secrets securely (Key Vault, environment variables, no hardcoded credentials).
  • Implement data lineage and audit instrumentation for compliance.
Collaboration & Communication:
  • Partner with Data Architects to translate design specs into production-ready pipelines.
  • Work closely with Data Analysts to optimize downstream consumption performance.
  • Communicate pipeline incidents and data issues clearly to business stakeholders.
  • Participate in on-call rotation to support production pipelines.
Senior-Level Expectations:
  • Own delivery of complex, multi-source pipelines with minimal direction.
  • Mentor junior and mid-level data engineers through pairing and code reviews.
  • Identify and drive technical debt reduction alongside feature delivery.
  • Contribute to and shape team standards, templates, and reusable components.
  • Influence tooling, framework, and platform decisions across the team.
Required Qualifications:
  • 8+ years of experience in data engineering or platform engineering roles.
  • Strong experience with Snowflake, Databricks, and dbt in production environments.
  • Advanced SQL and Python skills.
  • Experience building finance or regulated data pipelines at scale.
  • Preferred Qualifications
  • Telecom industry experience (ARPU, churn, prepaid/postpaid metrics).
  • Experience with both Azure and AWS cloud platforms.
  • Prior experience supporting financial reporting and period-end close cycles.
TekWissen Group is an equal opportunity employer supporting workforce diversity.

About the Company

T

TekWissen LLC

WE THE TEKWISSEN PEOPLE

TekWissen offers you a broader portfolio of services, industry-leading solutions, and the meaningful innovations that give you greater flexibility and speed to respond to market dynamics, reduced costs and risk to improve enterprise performance, and increased productivity to enable growth.

To keep pace with global market demands, TekWissen keeps its finger on the pulse of change. Our organized approach to guiding a project from its inception to closure. Managing projects is becoming more and more important as we enter the digital era. To cope with the pace that this transition demands, a method is required to manage projects so they can yield quality work, while incorporating efficient use of time and resources.

Project involves identifying which quality standards are relevant to the project and determining how to satisfy them.

It is important to perform quality planning during the Planning Process and should be done alongside the other project planning processes because changes in the quality will likely require changes in the other planning processes, or the desired product quality may require a detailed risk analysis of an identified problem. It is important to remember that quality should be planned, designed, then built in, not added on after the fact.

Capabilities and accomplishments in one TekWissen business enhance the opportunity for success in the others. Put simply, TekWissen's unique combination of attributes promotes success.



COMPANY SIZE
100 to 499 employees
INDUSTRY
Computer/IT Services
FOUNDED
2009
WEBSITE
http://www.tekwissen.com/