Senior Data Engineer

Job not on LinkedIn

🔥 0 minutes ago

🌏 Anywhere in the World

💵 $190k - $240k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 0%

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.

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Ready.net

WebsiteLinkedInAll Job Openings

1 - 10 employees

💼 Consulting

📦 Logistics

🏛️ Government

Consulting • Logistics • Government

Ready. net is a company that provides innovative software solutions tailored for government efficiency and broadband infrastructure development. The company offers a comprehensive platform for managing broadband, energy, and water grants, utilizing geospatial AI for efficient compliance, reporting, and collaboration. Ready. net specializes in automating and optimizing processes for government agencies, utility providers, and broadband operators to enhance resource allocation and streamline operations. Their services aim to increase efficiency, transparency, and engagement between stakeholders. Ready. net is committed to bridging the digital divide by empowering state broadband offices and other organizations to manage grants effectively, ensure digital equity, and connect underserved communities.

📋 Description

• Partner with product and engineering teams to understand requirements and translate them into technical architecture • Evaluate and recommend data tools, frameworks, and infrastructure choices • Contribute to roadmap discussions and build-vs-buy decisions • Design, implement, and maintain scalable AWS data infrastructure • Own data lake and warehouse architecture, including partitioning, storage optimization, and data lifecycle management • Build and maintain production-grade Apache Airflow DAGs for ingestion, transformation, and export workflows • Ensure observability through monitoring, alerting, and incident resolution • Build and maintain dbt pipelines with data quality checks and structured data modeling • Design and maintain database schemas for multi-state, multi-tenant program data • Write and optimize SQL queries across PostgreSQL, Redshift, and Athena • Develop reusable data models, utilities, and shared Python packages • Design infrastructure for large-scale time-series and event-based data • Implement ingestion, storage, and retrieval patterns for high-frequency temporal datasets • Work with vector databases for AI-powered features and semantic search • Integrate LLM workflows into ELT pipelines using AWS Bedrock, LangChain, and related frameworks • Build production AI-assisted data comparison, validation, and enrichment pipelines • Work with MLflow and deploy production-level ML pipelines • Monitor AI/ML tooling developments and bring relevant innovations to the team • Design automated data QA systems for dataset quality, completeness, and consistency • Implement cleansing and reconciliation routines for multi-source ingestion • Proactively monitor pipelines and resolve issues before downstream impact • Mentor junior and mid-level data engineers through code reviews, pair programming, and architectural guidance • Establish standards for code quality, testing, and documentation • Foster ownership, curiosity, and continuous improvement on the data team

🎯 Requirements

• 5+ years of data engineering experience with ownership and operational support of production systems end-to-end • Ability to evaluate technical trade-offs and make pragmatic architecture decisions balancing cost and performance • Strong proficiency in SQL, including PostgreSQL and Athena/Presto • Strong proficiency in Python and production-quality coding • Deep hands-on experience with AWS data services: S3, Athena, RDS, ECS, Lambda, IAM, and CloudWatch • Production experience with Apache Airflow or similar orchestration tools • Experience with large-scale time-series, event-based, or streaming data systems • Experience with version control using GitHub, Subversion, GitLab, or Mercurial • Familiarity with vector databases and LLM integration patterns such as LangChain and AWS Bedrock • Experience building data quality frameworks or automated validation systems • Demonstrated ability to mentor engineers and contribute to team culture • Excellent communication skills for explaining complex infrastructure decisions to non-engineers • Comfortable working with ambiguity and making first-principles decisions • Comfortable working across multiple time zones • Experience managing data for SaaS platforms is a plus • Experience with large-scale spatiotemporal data pipelines, including PostGIS, spatial indexing, and tiling, is a plus

🏖️ Benefits

• Competitive (and ever expanding) benefits for employees and dependents • Opportunities to learn and grow – all things startups • Work from anywhere you want, as long as you can get great internet • Optional, encouraged retreats 2–3 times per year • Opportunity to shape the benefits program • Meaningful equity upside