Job Description
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
Location: Frisco, TX, 75034
Duration: 6 Months
Job Type: Temporary Assignment
Work Type: Onsite
Job Description:
DATA PIPELINE DEVELOPMENT
- Architect, design, and oversee development of enterprise-scale ELT/ETL pipelines for finance and revenue data (billing, revenue, GL, opex).
- Define and enforce standards for batch, incremental, and streaming ingestion patterns (CDC, watermarking, event-driven ingestion).
- Ensure idempotent, fault-tolerant, and highly scalable pipeline design across platforms.
- Establish frameworks for error handling, retry strategies, dead-letter queue patterns, and operational resiliency.
- Provide technical leadership for multi-source, high-volume data integration pipelines.
PLATFORM & TOOLING
- Lead architecture and adoption of Snowflake and Databricks platforms for large-scale data processing and analytics.
- Define best practices for:
- Snowflake (Snowpipe, streams, tasks, query optimization, cost efficiency)
- Databricks (PySpark, Delta Live Tables, Unity Catalog, job optimization)
- dbt (modular design, testing frameworks, CI/CD integration, reusable components)
- Establish and govern orchestration frameworks using Airflow / Azure Data Factory, including DAG standards, dependency design, and monitoring.
- Evaluate and drive tooling strategy and platform standardization across teams.
CLOUD INFRASTRUCTURE
- Architect and optimize cloud-native data platforms on Azure (ADLS Gen2, Event Hub, ADF, Key Vault) or AWS equivalents.
- Define standards for infrastructure-as-code (Terraform, Bicep) and environment provisioning.
- Drive cost optimization strategies (compute sizing, storage design, partitioning, workload isolation).
- Ensure platforms are scalable, secure, and production-ready.
LANGUAGES & FRAMEWORKS
- Provide deep technical leadership in:
- Advanced SQL (query tuning, execution optimization, complex transformations)
- Python / PySpark for distributed data processing
- Guide teams on best practices, reusable frameworks, and performance optimization.
- Oversee development standards for Spark, Scala (where applicable), and automation scripting.
STREAMING & REAL-TIME
- Architect real-time and near real-time data processing solutions using Kafka / Event Hub and Spark Structured Streaming.
- Define patterns for stateful processing, watermarking, checkpointing, and fault tolerance.
- Lead implementation of real-time finance/revenue use cases such as reconciliation, anomaly detection signals, and operational reporting.
DATA QUALITY & TESTING
- Establish enterprise frameworks for data quality, validation, and observability.
- Define standards for:
- Automated testing (unit, integration, regression)
- Data validation (completeness, accuracy, consistency)
- Data quality tools (dbt tests, Great Expectations, custom frameworks)
- Ensure SLA monitoring, alerting, and data freshness tracking across all pipelines.
- Drive proactive data quality and governance practices across teams.
DATA MODELING SUPPORT
- Interpret and implement architect-defined enterprise data models (star, snowflake, data vault).
- Provide guidance on:
- SCD (Type 1/2) strategies
- Partitioning, clustering, and performance optimization
- Collaborate with architects to evolve scalable and reusable data models.
- Support semantic layer enablement for analytics and reporting.
DEVOPS & ENGINEERING PRACTICES
- Define and enforce CI/CD standards for data engineering (GitHub Actions, Azure DevOps).
- Establish code quality, versioning, and deployment best practices (branching strategies, PR reviews, release pipelines).
- Standardize environment promotion (dev QA prod) and release management.
- Drive adoption of engineering excellence practices including reusable frameworks and templates.
SECURITY & GOVERNANCE
- Lead implementation of enterprise-grade security and governance controls:
- RBAC, row/column-level security
- PII and CPNI compliance (TISS-310)
- Define standards for secrets management and secure pipeline design.
- Ensure data lineage, auditability, and compliance readiness across platforms.
FINANCE DOMAIN KNOWLEDGE
- Deep understanding of finance and revenue data domains, including:
- Billing and revenue systems
- GL structures and financial reporting
- Revenue recognition and reconciliation
- Period-end close cycles
- Guide engineering teams on accurate implementation of finance logic.
- Ensure high data integrity standards for regulated financial data.
SOFT SKILLS & COLLABORATION
- Act as a technical leader and escalation point across engineering teams.
- Partner with architects, product managers, analysts, and business stakeholders.
- Drive cross-team alignment and solution consistency.
- Communicate complex technical topics clearly to both technical and non-technical audiences.
- Lead incident reviews and ensure continuous improvement.
TekWissen Group is an equal opportunity employer supporting workforce diversity.
Numbers & Facts
| Location | Frisco, TX |
| Industry | Computer/IT Services |
| Salary | $52.11 |
| Company Size | 100 to 499 employees |
| Year Founded | 2009 |
| Website | http://www.tekwissen.com/ |
About Company
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.Skills
- Best Practicesunmatched
- Billingunmatched
- Centers for Disease Control and Prevention (CDC)unmatched
- Cisco Unityunmatched
- Cloud Computingunmatched
- Continuous Deployment/Deliveryunmatched
- Continuous Improvementunmatched
- Continuous Integrationunmatched
- Cost Controlunmatched
- Data Analysisunmatched
- Data Managementunmatched
- Data Modelingunmatched
- Data Processingunmatched
- Data Qualityunmatched
- Database Extract Transform and Load (ETL)unmatched
- DevOpsunmatched
- Diversityunmatched
- Enterprise Protectionunmatched
- Error Handlingunmatched
- Financeunmatched
- Financial Reportingunmatched
- GitHubunmatched
- Incident Managementunmatched
- Information Technology & Information Systemsunmatched
- Integration Testingunmatched
- Machine Toolunmatched
- Microsoft Windows Azureunmatched
- Multiplatform/Cross-Platformunmatched
- Operational Expenditure (OPEX)unmatched
- People Managementunmatched
- Performance Tuning/Optimizationunmatched
- Press Releasesunmatched
- Process Improvementunmatched
- Python Programming/Scripting Languageunmatched
- Query Optimizationunmatched
- Reconciliationunmatched
- Regression Testingunmatched
- Revenue Recognitionunmatched
- SQL (Structured Query Language)unmatched
- Sales Pipelineunmatched
- Scala Programming Languageunmatched
- Scripting (Scripting Languages)unmatched
- Service Level Agreement (SLA)unmatched
- Snowflake Schemaunmatched
- Standards Developmentunmatched
- Standards Strategyunmatched
- Star Schemaunmatched
- Team Playerunmatched
- Technical Leadershipunmatched
- Test Automationunmatched
- Test Designunmatched
- Unit Testunmatched
- Use Casesunmatched
- Workforce Managementunmatched
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