Data Analytics Engineer

Tundra Technical Solutions; United States; On-site; USD 120,000 - 170,000; Full time

Job summary

Tundra Technical Solutions is seeking an analytics engineer to design and optimize analytics infrastructure in support of regulated environments. You will own data pipelines, implement robust SQL transformations, and collaborate with cross-functional teams to deliver reliable, business-ready insights.

You have 5+ years in analytics or data engineering, strong Python skills, experience with dbt and Airflow, and a practical mindset for data quality and governance.

Qualifications

• Minimum 5 years of relevant experience in analytics engineering, data engineering, or data-heavy technical roles (level dependent).
• Advanced SQL skills (complex transformations, performance tuning, data quality checks).
• Experience building and maintaining ETL/ELT pipelines and data models (e.g., dbt, Airflow, or equivalent orchestration/transformation tools).
• Working Python skills for automation, pipelines, and analysis
• Demonstrated ability to execute on ambiguous, cross-functional projects with clear written and verbal communication.
• High ownership mindset with strong attention to detail and comfort operating in regulated environments.
• Demonstrates the ability to responsibly use generative AI tools and copilots in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.

Skills

Advanced SQL

Python

ETL/ELT pipelines

Data modeling

dbt/Airflow

Communication

Generative AI in workflows

Tools

dbt

Airflow

Snowflake/Databricks

GitHub CI/CD

Data observability tools

Job description

What we look for in you (ie. job requirements):

• Minimum 5 years of relevant experience in analytics engineering, data engineering, or data-heavy technical roles (level dependent).
• Advanced SQL skills (complex transformations, performance tuning, data quality checks).
• Experience building and maintaining ETL/ELT pipelines and data models (e.g., dbt, Airflow, or equivalent orchestration/transformation tools).
• Working Python skills for automation, pipelines, and analysis
• Demonstrated ability to execute on ambiguous, cross-functional projects with clear written and verbal communication.
• High ownership mindset with strong attention to detail and comfort operating in regulated environments.
• Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human‑in‑the‑loop practices to deliver business‑ready outputs and drive measurable improvements in efficiency, cost, and quality.

Nice to haves:

• Domain experience in BSA/AML, Transaction Monitoring, sanctions screening, KYC/EDD, fraud, or investigations.
• Familiarity with Snowflake/Databricks and modern warehouse/lakehouse patterns.
• Experience with GitHub-based workflows, CI/CD for data, and data observability tools.
• Applied statistics/experimentation, root‑cause analysis, or detection performance measurement.
• Interest in crypto, blockchain analytics, or on‑chain/off‑chain data integration.