Senior Data Engineer (Pipelines & Analytics)

Softadom; United States; Remote; USD 140,000 - 180,000; Full time

Job summary

Softadom is seeking a senior data engineer to build robust data pipelines and ensure data quality as schemas evolve and volumes grow. You will handle ingestion, modeling, testing, and operational reporting for analytics and BI, working closely with cross-functional teams and documenting progress incrementally.

You will design end-to-end pipelines using dbt with BigQuery or Snowflake, orchestrate with Airflow or Dagster, and collaborate with engineers, analysts, and leadership to align KPI

Qualifications

• Senior-level experience building production data pipelines.
• Hands-on with dbt and at least one orchestrator (Airflow or Dagster).
• Experience with cloud warehouses (BigQuery or Snowflake) and reverse-ETL tooling.
• Comfort ingesting from relational databases, SaaS APIs, event streams, and files.

Responsibilities

• Ingest data from PostgreSQL databases, SaaS APIs, event streams, and flat files into analytics platforms.
• Model data for analytics and operational reporting using dbt with BigQuery or Snowflake.
• Implement automated tests that detect schema drift and data quality issues.
• Orchestrate pipelines with Airflow or Dagster and apply reverse-ETL tooling where appropriate.
• Partner with backend engineers, analysts, and leadership on KPI definitions.

Skills

Senior data engineer

dbt

Airflow

Dagster

BigQuery

Tools

BigQuery

Snowflake

PostgreSQL

Job description

Role overview

This senior position focuses on building data pipelines that remain trustworthy as schemas shift, backfills occur, and data volumes grow—rather than dashboards stacked on fragile exports. The work spans ingestion, modeling, testing, and operational reporting for analytics and business intelligence needs. It is a good fit for a senior engineer who enjoys cross-functional partnership, clear documentation, and incremental delivery as much as technical depth.

Responsibilities

• Ingest data from PostgreSQL databases, SaaS APIs, event streams, and flat files into analytics platforms
• Model data for analytics and operational reporting using tools such as dbt alongside BigQuery or Snowflake
• Implement automated tests that detect schema drift and data quality issues before stakeholders notice
• Orchestrate pipelines with Airflow or Dagster, and apply reverse-ETL tools where appropriate
• Partner with backend engineers on event design, with analysts on semantic layers, and with leadership on KPI definitions

Requirements

• Senior-level experience building and operating production data pipelines
• Working knowledge of dbt and at least one orchestrator such as Airflow or Dagster
• Familiarity with a cloud warehouse such as BigQuery or Snowflake, plus reverse-ETL tooling
• Comfort ingesting from relational databases, SaaS APIs, event streams, and files
• Strong documentation habits and a commitment to incremental, testable delivery

Nice to have

• Experience designing event schemas in collaboration with backend engineering teams
• Ability to define and refine KPI definitions with non-technical stakeholders