Senior Data Science Analyst/ Data Engineer

Pinnacle Group; Richmond (VA); Hybrid; USD 110,000 - 170,000; Full time

Job summary

PTR Global is seeking a Senior Data Engineer to design, build, and optimize enterprise-scale data pipelines in Richmond, VA. You will lead ELT/ETL processes, implement streaming and batch workflows, and drive data quality, security, and observability across systems.

The role requires hands-on coding in SQL, Python, and shell, plus experience with Snowflake, Oracle Exadata, Kafka, and cloud data warehouses. Collaboration with governance, DataOps, and architecture teams is essential.

Qualifications

• Advanced SQL, ELT patterns, and tuning for large data platforms.
• Experience with cloud/on-prem data warehouses (Snowflake, Exadata).
• Hands-on ETL/ELT tools such as Talend, dbt, Informatica.
• Deep data warehousing and dimensional modeling knowledge.
• Designing and supporting production data pipelines at scale.
• Scripting in Python and shell; strong CI/CD and DataOps familiarity.
• Experience with data virtualization and streaming (Kafka, Kinesis, Spark Streaming).
• Familiar with governance, metadata, lineage and security requirements.

Responsibilities

• Build end-to-end data pipelines and ETL/ELT solutions for analytics and AI/ML use cases.
• Develop batch and streaming workflows with scalable, low-latency patterns.
• Optimize data modeling, transformations, and performance tuning.
• Evaluate, select, and integrate tooling to meet project needs.
• Create complex, high-volume pipelines using SQL-centric patterns.
• Design scalable streaming pipelines for real-time data delivery.
• Lead performance tuning across pipelines, warehouses, and workloads.
• Ensure resilience, observability, and production readiness.
• Implement robust error handling, restarts, and monitoring.
• Maintain streaming pipelines using Kafka, Kinesis, Spark Streaming.
• Perform on-the-fly data cleaning, validation, and enrichment.
• Apply indexing/partitioning to improve query response and scalability.
• Uphold data quality checks, validation, and reconciliation.
• Ensure security, access control, and governance compliance.
• Collaborate with governance & DataOps on metadata and lineage.
• Document standards and coding practices; participate in code reviews.
• Work with infra, apps, and architecture teams on complex transformations.
• Translate ambiguous requirements into solid technical designs.
• Handle multi-platform environments across multiple projects.

Skills

SQL

ELT patterns

Performance tuning

Python

Shell

CI/CD

Observability

DataOps

Data modeling

Dimensional modelling

Education

Bachelor's degree or higher

Discipline: CS/IS/Math

Tools

Oracle Exadata

Snowflake

Talend

dbt

Informatica

Kafka

Kinesis

Spark Streaming

Flink

Denodo

Dremio

Starburst

Cribl

Job description

Senior Data Scientist Analyst/ Data Engineer
IT | Software Design/Developer Richmond , Virginia Contract Oct 29, 2026

Position: Data Science Analyst/ Data Engineer
Location: Richmond Virginia 23219 (Hybrid)
Duration: 12 months
Job ID: 180986

High Level Project Overview:

Role Summary:

• The Senior Data Engineer is a handson expert and technical leader, actively engaged in designing, building, and optimizing scalable, reliable data pipelines at an enterprise level.
• This role not only guides architectural decisions but also directly implements advanced ELT solutions, troubleshoots complex data challenges, and ensures best practices through practical, highimpact contributions.
• This role combines deep handson expertise with technical ownership, mentoring, and architectural alignment.
• The Senior Data Engineer drives and implements data engineering best practices, ensures high standards for quality and security, and partners with architecture and platform teams to improve the overall data ecosystem.

Key Responsibilities:

• Build endto-end data pipelines and ETL/ELT solutions to support analytics, reporting, and AI/ML use cases, ensuring solutions are robust and production-ready through practical implementation.
• Apply scalable patterns for batch and incremental processing by developing, testing, and deploying data workflows, focusing on handson coding and troubleshooting.
• Review and implement data modeling, transformation logic, and performance strategies, using deep technical expertise to optimize and validate solutions.
• Evaluate, select, and integrate tooling, frameworks, and platform capabilities by actively prototyping and configuring systems to meet project requirements.
• Build up complex, highvolume data pipelines using SQL-centric ETL/ELT patterns.
• Design and implement scalable streaming pipelines to process realtime data, ensuring low latency and reliable delivery for analytics and operational use cases.
• Lead performance tuning efforts across pipelines, warehouses, and workloads.
• Ensure data pipelines are resilient, observable, and production ready.
• Implement enterprisegrade error handling, restart ability, and monitoring.
• Build and maintain scalable, lowlatency streaming data pipelines using technologies such as Kafka, Kinesis, or Spark Streaming
• Perform onthe-fly data cleaning, validation, and enrichment before data reaches its final destination.
• Uses strategies such as Indexing and partitioning to fine tune the data warehouse and big data environments to improve the query response time and scalability
• Implement standards for data quality checks, validation, and reconciliation.
• Ensure pipelines meet security, access control, and governance requirements.
• Partner with governance & DataOps teams on metadata, lineage, and auditability.
• Apply consistent naming conventions, documentation, and coding standards.
• Improve operational monitoring, alerting, and incident response processes.
• Proactively identify reliability, performance, and cost optimization opportunities.
• Support and guide production troubleshooting and root cause analysis.
• Investigating data quality incidents and identifying design/coding GAPs
• Participate in design and code reviews to enforce quality and best practices.
• Partner with various infrastructure teams, application teams, and architects to generate process designs and complex transformations to various data elements to provide the Business with insights into their business processes.
• Translate ambiguous requirements into well designed technical solutions.
• Work in complex multiplatform environments on multiple project assignments.

Required Years of Experience:

• Must have 5 to 7 plus years of Data Engineering experience.

Education:

• Education: Bachelors or higher required
• Discipline: Computer Science, Information Systems, Mathematics

Required Skills and Experience:

• Advanced expertise in SQL, ELT patterns, and performance tuning.
• Strong experience with Oracle Exadata, Snowflake or similar cloud/on prem data warehouses.
• Hands on experience with enterprise ETL/ELT platforms (e.g., Talend, dbt, Informatica).
• Deep understanding of data warehousing architecture and dimensional modeling.
• Experience designing and supporting large scale, production data pipelines.
• Strong scripting experience (Python, shell).
• Experience with data virtualization tools (e.g., Denodo, Composite, dremio, Starburst).
• Experience with DataOps practices, CI/CD, and observability.
• Required 5 to 7 plus years of Data Engineering experience.
• ETL Development and Process Support, may require weekend/off business hours work.

Key Behavioral Expectations ("How We Work"):

• Delivering at Pace: Acts with urgency to meet deadlines while maintaining quality, prioritizing workload effectively under pressure.
• Collaborative Teamwork: Actively supports colleagues, shares knowledge freely, and treats others with dignity and respect.
• Effective Communication: Tailors communication style to the audience, ensuring clarity and transparency in both successes and challenges.
• Ownership and Adaptability: Takes responsibility for outcomes and welcomes feedback for improvement.
• Ability to work independently
• Achievement orientation
• Selfstarter
• Concern for quality
• Flexibility

Preferred / Nice to Have:

• Experience supporting AI/ML or advanced analytics pipelines.
• Cloud platform experience (AWS, Azure, or GCP).
• Prior experience influencing enterprise data standards or reference architecture.
• Experience optimizing cost and performance in cloud data warehouses.
• Handson experience with Cribl, Apache Kafka, Kafka Connect, Spark Streaming, or Apache Flink

About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit www.ptrglobal.com

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