Stacktics is looking for a Data Engineer (GCP) to join our Data Systems team. We build industry-leading Cloud Infrastructure and Analytics solutions, heavily focused on the marketing and digital ecosystem space.
In this role, you won't be maintaining legacy Hadoop clusters or writing massive Spark jobs. You will be operating a highly modern, SQL-heavy ELT stack on Google Cloud Platform. You will live and breathe Google BigQuery, Apache Airflow (Python DAGs), and Dataform, transforming complex marketing data into clean, highly performant dimensional models that drive our business and client success.
What You Will Do Every Day (Key Responsibilities)
Pipeline Orchestration: Design, write, and deploy idempotent Python DAGs via Apache Airflow (Cloud Composer) to extract data from various marketing APIs and manage complex task dependencies.
In-Warehouse ELT (Dataform): Own the "Transform" step by writing scalable, modular SQL inside Google Cloud Dataform. You will build incremental models, manage dependencies, and apply software engineering best practices to our data warehouse.
BigQuery Mastery: Write, optimize, and maintain complex Scheduled Queries in BigQuery. You will proactively manage query performance and compute costs using partitioning, clustering, and smart data modeling.
Data Quality & Reliability: Implement automated testing and data quality assertions directly into the pipeline to catch anomalies before they reach downstream dashboards.
CI/CD & DevOps: Treat data as code. You will manage your Dataform and Airflow codebases using Git, participate in peer code reviews, and utilize CI/CD pipelines to deploy to staging and production safely.
Marketing Analytics Collaboration: Transform messy digital ecosystem data (Google Analytics, Facebook Ads, Salesforce) into business-ready tables for attribution modeling, audience segmentation, and A/B testing.
What You Bring to the Table (Qualifications)
5+ years in Data Engineering, with a strong focus on cloud-native data warehousing (Google BigQuery is highly preferred, but Snowflake or Redshift translates well).
Expert-Level SQL: You are highly comfortable with CTEs, window functions, complex joins, and handling semi-structured data (JSON/Structs).
Python for Data Engineering: You know how to write clean Python code to interact with REST APIs and orchestrate workflows via Apache Airflow.
Modern Transformation Tools: Hands-on experience with Dataform or dbt (data build tool) is essential. You understand the shift from traditional ETL to modern ELT.
Engineering Rigor: You are comfortable using Git, command-line tools, and understand the core concept of pipeline idempotency.
Domain Knowledge: A strong understanding of digital marketing concepts (cookie-based collection, attribution, audience segments) is a massive asset.
Company-Wide Responsibilities
Adapt to ever-changing client needs and maintain dedication toward achieving excellence in Stacktics' deliverables.
Be an enthusiastic, positive, and constantly curious team player who is comfortable presenting technical concepts to internal and external stakeholders.
What else you need to know: