Description
What Youll Need
Own the architecture and evolution of the data platform across transactional, streaming, and analytical systems
Design and operate scalable data systems on AWS, including Aurora PostgreSQL, Redis, and event-driven pipelines
Build and optimize data flows between operational systems and analytics platforms (e.g., Snowflake, observability and product analytics tools)
Ensure data integrity, consistency, and availability across distributed systems
Design for high-throughput, low-latency data processing supporting real-time and near-real-time use cases
Establish data modeling standards, governance practices, and access patterns across the organization
Drive improvements in data observability, monitoring, and incident response
Partner with DevOps, product, and business teams to translate data needs into scalable technical solutions
Lead complex initiatives such as data correlation across systems, unified event models, and cross-platform insights
Identify and resolve bottlenecks, scaling challenges, and data quality issues
Mentor engineers and elevate data engineering practices across the organization
- Transactional & In-Memory Data Storage (Core Ecosystem)
AWS Aurora PostgreSQL: Serves as the primary operational database managing digital commerce and transactional order context.
Code/Practices: Advanced PL/pgSQL, connection pooling optimization, partition schema design for transactional data, tuning vacuum settings, and index strategy optimization
Redis: Leveraged as the distributed in-memory cache and state manager to support low-latency requirements on high-volume consumer apps.
Code/Practices: Key-value eviction strategies, cluster configuration, data structure caching routines (Hashes, Sorted Sets), and handling distributed cache-stampede mitigation.
Flyway / Liquibase: Database schema migration and version control tooling utilized natively to evolve transactional database architecture alongside continuous app development.
- High-Throughput Streaming & Event-Driven Processing
AWS Kinesis / Apache Kafka: Infrastructure underpinning real-time and near-real-time streaming applications.
Code/Practices: Managing stream partitioning, offset tracking, consumer lag remediation, schema registry integration (Avro/JSON Schema), and message serialization/deserialization.
Python: The foundational language used across custom automation scripts and microservices infrastructure.
Code/Practices: Object-oriented programming, utilizing concurrency modules (asyncio, multiprocessing), building API integration logic, and strict custom unit-testing suites.
- Big Data Transformation & Analytical Storage
Snowflake: Core corporate multi-cluster data platform serving all downstream business analytics, data science, and operational visibility workloads.
Code/Practices: Writing complex analytical Window functions, executing optimized micro-partitioning queries, dynamic data masking, managing virtual warehouse clustering, and building zero-copy clones.
The default transformation layout to convert raw staging data into clean data warehouse structures.
Code/Practices: Developing core modular SQL models, writing customized schema-testing configurations (data_tests), managing documentation builds, and structuring semantic dimensional tables (Star Schema/Data Vault 2.0).
Apache Airflow / Dagster: Centralized DAG system orchestrating cross-system dependencies, sensor alerts, and workflow execution.
- Observability & Data Infrastructure
AutomationData Quality & Monitoring Suites: Tools (such as AWS CloudWatch, Datadog, Great Expectations, or Monte Carlo) used to drive end-to-end operational visibility and data pipeline monitoring.
Code/Practices: Creating customized alerting metrics, synthetic anomaly detection triggers, tracking consumer behavior trends, and telemetry ingestion logs.
Terraform: Primary declarative Infrastructure-as-Code (IaC) tool for managing cloud state and deploying data architecture.
Code/Practices: Writing modular HCL (HashiCorp Configuration Language) manifests to scale Amazon RDS instances, secure IAM roles, and spin up storage policies.
Foundation of automated delivery systems.Code/Practices: Designing semantic release pipelines, multi-environment infrastructure tracking (dev, staging, prod), and formatting custom linting checkpoints.
Skills
Python, Aws, snowflake, airflow, rags, mlops, aws bedrock, dagster, Prefect, Immuta, Debezium, Golang, Scala
Top Skills Details
Python,Aws,snowflake,airflow,rags,mlops,aws bedrock
Additional Skills & Qualifications
Advanced Stack (Nice-to-Haves) Streaming Extensions: Debezium (Change Data Capture/CDC to pull changes from databases instantly).
Performance Code: Go (Golang) or Scala (fast microservices for heavy traffic).
Orchestration & AI: Dagster or Prefect (modern pipeline workflows), MLflow or Feast (MLOps feature stores).
Governance & Testing: Immuta (PII data masking), Great Expectations or Soda
Experience Level
Expert Level
Job Type & LocationThis is a Permanent position based out of Addison, TX. Pay and BenefitsThe pay range for this position is $175000.00 - $200000.00/yr. Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors.FLAVOR PERKS:
Unlimited paid time off for exempt employees One paid volunteer day of your choice Competitive bonus structure for eligible roles Team member stock purchase plan Health savings or flexible spending account options 401k (dollar for dollar on the first 3% and then 50 cents on the dollar for the next 2% for team member contributions up to 5% of eligible compensation) Comprehensive medical, dental, and vision benefits Basic life and AD&D insurance provided Pet insurance Education Assistance Wellness reimbursement program Paid maternity and paternity leave Job Type & LocationThis is a Permanent position based out of Addison, TX. Application DeadlineThis position is anticipated to close on Nov 16, 2026. Workplace TypeThis is a fully onsite position in Addison,TX.
About TEKsystems
We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is an Allegis Group company.
The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
About TEKsystems and TEKsystems Global Services
Were a leading provider of business and technology services. We accelerate business transformation for our customers. Our expertise in strategy, design, execution and operations unlocks business value through a range of solutions. Were a team of 80,000 strong, working with over 6,000 customers, including 80% of the Fortune 500 across North America, Europe and Asia, who partner with us for our scale, full-stack capabilities and speed. Were strategic thinkers, hands-on collaborators, helping customers capitalize on change and master the momentum of technology. Were building tomorrow by delivering business outcomes and making positive impacts in our global communities. TEKsystems and TEKsystems Global Services are Allegis Group companies. Learn more at TEKsystems.com.
The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records.
Massachusetts Lie Detector: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.