Staff Data Engineer: AI-Driven Home Data Platform (Remote)

Acceler8 Talent

Houston (TX)

Hybrid

USD 200,000 - 300,000

Full time

14 days+
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Benefits offered by this job

Competitive compensation up to $250,000
Foundational role as the first Staff Data Engineer
Opportunity to work closely with the Head of Data

Job summary

A dynamic tech startup is seeking a Staff Data Engineer to architect and build a core data platform. This role calls for a candidate with extensive experience in creating scalable data pipelines and a robust background in modern infrastructure. You will work closely with various teams to drive data-driven decision making and establish data governance. Competitive compensation is offered, reaching up to $250,000 depending on experience and location.

Qualifications

  • 8+ years of experience as a software or data engineer, focused on large-scale data systems.
  • Deep expertise in building and maintaining data pipelines for analytics or ML.
  • Strong understanding of CI/CD and infrastructure-as-code practices.

Responsibilities

  • Architect and build the core data platform for intelligence.
  • Design and implement scalable data pipelines across diverse sources.
  • Collaborate with AI/ML, product, and engineering teams for data-driven decisions.

Skills

Building and maintaining data pipelines
ETL frameworks (Python, Spark, Airflow, dbt)
SQL proficiency
Cloud-native data platforms (AWS preferred)
Data modeling
CI/CD best practices
Software engineering fundamentals

Tools

Redshift
S3
Spark
Airflow
dbt
Kafka
Databricks
Snowflake

Job description

A dynamic tech startup is seeking a Staff Data Engineer to architect and build a core data platform. This role calls for a candidate with extensive experience in creating scalable data pipelines and a robust background in modern infrastructure. You will work closely with various teams to drive data-driven decision making and establish data governance. Competitive compensation is offered, reaching up to $250,000 depending on experience and location.
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