DBT Analytics Engineer

Mastech Digital, Inc.
Pittsburgh, United States of America
5 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote
Pittsburgh, United States of America

Tech stack

Airflow
Amazon Web Services (AWS)
Business Analytics Applications
Data analysis
BigTable
Google BigQuery
Cloud Database
Continuous Integration
Data Governance
Relational Databases
Dimensional Modeling
Python
Package Management Systems
Performance Tuning
Standard Sql
SQL Databases
Tableau
Snowflake
GIT
Kubernetes
Data Management
Looker Analytics
Software Version Control
Redshift
Databricks

Job description

This is a high?impact role where you'll work directly with business teams, own end?to?end data models, and help shape a future?ready analytics platform. If you have strong AWS, DBT, SQL, and Databricks experience, this could be a great fit., What You'll Do

Design and implement robust dimensional and relational data models.

Build and maintain scalable dbt transformation pipelines.

Own transformation and modeling of curated (Silver/Gold) datasets.

Collaborate with analysts, product analytics, data scientists, and stakeholders.

Implement data quality tests, monitoring, SLAs, and alerting.

Partner with Data Engineers to define and enforce data contracts.

Follow analytics engineering best practices (version control, testing, documentation).

Requirements

5+ years in analytics engineering, data modeling, or similar roles.

Expert-level SQL skills (optimization & performance tuning).

Extensive dbt experience (testing, documentation, package management).

Strong Python programming skills.

Deep understanding of dimensional modeling (star schemas, one big table).

Experience with cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks).

Familiarity with Airflow and orchestration frameworks.

Experience with Git and CI/CD for analytics code.

Strong business acumen and ability to translate requirements into data models.

Knowledge of data governance, privacy, compliance (GDPR, CCPA, SOX).

Familiarity with BI tools (Tableau, Looker, Mode).

Strong ownership mindset and communication skills.

Dedication to data quality, documentation, and enabling self-service analytics.

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