Description

Key Responsibilities

Design, build, and maintain robust ELT/ETL pipelines ingesting data into BigQuery.

Configure and extend Fivetran connectors; develop custom connectors when required.

Develop and maintain dbt models, tests, and documentation to ensure data quality and lineage.

Monitor pipeline health, implement alerting, and respond to incidents to ensure data freshness.

Partner with the Senior Data Architect on data governance practices (cataloguing, certification, access controls).

Optimize BigQuery tables for cost efficiency and query performance (partitioning, clustering, materialization).

Collaborate with Analytics Engineers and Analysts to align data models with downstream requirements.

Contribute to CI/CD pipelines and infrastructure-as-code practices for data assets.

Document data flows, dependencies, and pipeline architecture for transparency and team alignment.

Qualifications

3+ years of experience in data engineering or related roles.

Strong proficiency in SQL and Python for pipeline development and debugging.

Hands-on experience with BigQuery or other cloud data warehouses (Snowflake, Redshift, etc.).

Experience with ELT/ETL tools (Fivetran, Airbyte, or custom frameworks).

Proficiency with dbt for transformations and testing.

Experience with workflow orchestration tools (Airflow, Cloud Composer, Prefect).

Familiarity with GCP services (Cloud Storage, Pub/Sub, Cloud Functions) or equivalent AWS/Azure services.

Strong understanding of data modeling concepts (star schema, SCDs, normalization).

Fluent in English (written and spoken).

Nice to Have

Experience integrating Salesforce, HubSpot, or Stripe data sources.

Knowledge of data governance tools (GCP Data Catalog, Dataplex).

Experience with streaming pipelines (Pub/Sub, Kafka).

Familiarity with Terraform or other IaC tools.

Background in Revenue Operations or go-to-market data contexts.

Contributions to open-source data projects or dbt packages

Key Skills

Education

Bachelor's degree