Data Engineer

Job not on LinkedIn

🕒 July 28

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 13%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Ambush

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2015

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Ambush is a People Company that specializes in identifying, retaining, and integrating highly-talented remote designers and engineers into teams across various sectors. With almost a decade of experience, Ambush focuses on building long-term, dedicated partnerships, providing clients with exceptional software development and design services. The company prides itself on its human-centered approach, remote team integration, and commitment to quality, making it a trusted partner for organizations in the financial, medical, and privacy sectors.

📋 Description

• Join a people-first company where talented individuals build meaningful products • Collaborate with a team that values support, trust, and empowerment • Use strong engineering, design, and strategy skills to achieve bigger outcomes • Pursue long-term goals in a cooperative environment

🎯 Requirements

• Data pipeline / ETL & ELT engineering • Data orchestration & workflow management • Medallion / lakehouse architecture (Bronze → Silver → Gold) • Database & warehouse migration (OLTP → OLAP) • Data modeling • Data quality, validation & data contracts • Data integrity & idempotency (deterministic IDs, exactly-once semantics) • Change Data Capture (CDC) & event-driven pipelines • Observability, monitoring & alerting • Orchestration: Dagster (also Airflow, Prefect) • Data warehouse / OLAP: ClickHouse, PostgreSQL / Amazon Aurora • Transformation: dbt, Python (pandas, PyArrow, Pydantic, SQLAlchemy) • Open table formats / lakehouse: Apache Iceberg, Delta Lake, DuckDB, Apache Parquet • Data quality: Great Expectations, Soda, dbt tests • Senior-level