Data Engineer

🕒 August 31

🇺🇸 United States – Remote

💵 $150k - $180k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 11%

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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AHEAD

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💼 Consulting

🤖 Artificial Intelligence

🏢 Enterprise

💰 $5.7M Venture Round - AHEAD on 2024-05

Consulting • Artificial Intelligence • Enterprise

AHEAD is a technology consulting and systems-integration firm that accelerates digital transformation by engineering integrated solutions across infrastructure, applications, data, and security. The company specializes in AI transformation and AI-enabled infrastructure, data platform and platform/workload modernization, secure and resilient architectures, operational excellence, and managed services including IT lifecycle and procurement (AHEAD Hatch) and hardware integration (AHEAD Foundry). AHEAD delivers end-to-end services from strategy and financial consulting to build and run operations, partners with major cloud and infrastructure vendors (AWS, Google Cloud, Microsoft, Cisco, Dell, VMware, NVIDIA, ServiceNow, Palo Alto Networks, Rubrik, etc. ), and serves enterprise clients across industries such as healthcare, financial services, manufacturing, retail, and public sector.

📋 Description

• Build, maintain, and improve batch and low-latency data ingestion pipelines • Use approved AI coding tools and agents for code generation, refactoring, explanation, review, testing, documentation, troubleshooting, and operational support, with human validation • Develop SQL and Python solutions to collect, validate, transform, and publish data • Use Snowflake and dbt for transformations, reusable models, curated datasets, and data products • Translate business and technical requirements into source mappings, data models, acceptance criteria, and engineering solutions • Partner with analytics, application, AI, Integration Platform, and business teams • Apply data quality checks for completeness, freshness, uniqueness, consistency, and referential integrity • Add metadata, documentation, lineage, ownership, and usage guidance to data products • Implement secure access patterns, including role-based access, classification tags, masking, and row- or column-level controls • Build automated tests and deployment processes across development, QA, and production • Monitor pipeline health, data freshness, performance, and failures; troubleshoot issues and participate in incident resolution • Optimize Snowflake workloads, queries, transformations, and storage for performance, reliability, and cost • Support cross-system data curation for reporting, automation, shared business context, and AI use cases • Work with Integration Platform and semantic-layer capabilities, including Horizon • Participate in backlog refinement, estimation, code review, documentation, and Agile delivery • Identify opportunities to simplify delivery, reduce duplicate work, improve standards, and strengthen reliability

🎯 Requirements

• Bachelor’s degree in computer science, information systems, engineering, mathematics, or a related field, or equivalent experience • 3 or more years of experience in data engineering, software engineering, analytics engineering, or a related technical role • Professional experience writing production-quality SQL and Python • Experience building or supporting data pipelines, transformations, and data models in a cloud data environment • Experience with Snowflake, dbt, or comparable cloud data warehouse and transformation technologies • Understanding of data modeling, ELT/ETL patterns, pipeline orchestration, APIs, and source-system integration • Experience with source control, code review, automated testing, and CI/CD • Demonstrated active use of AI-assisted software development tools for code generation, test creation, documentation, debugging, or review • Ability to follow an AI SDLC and identify opportunities for multiple cooperating agents to improve delivery • Understanding of data quality, metadata, lineage, access control, privacy, and secure handling of enterprise data • Ability to investigate data issues, communicate findings clearly, and work through ambiguity • Ability to collaborate with engineers, analysts, product owners, governance partners, security teams, and business stakeholders • Preferred: Experience with Azure services, serverless functions, cloud storage, or other cloud-native data engineering capabilities • Preferred: Experience with REST or GraphQL APIs and enterprise applications such as Salesforce, Hatch, or NetSuite • Preferred: Familiarity with orchestration, event-driven processing, observability, data catalogs, lineage tooling, or data quality platforms • Preferred: Experience supporting semantic models, MCP-based access, or governed interfaces • Preferred: Experience with master data, reference data, entity resolution, or shared business definitions • Preferred: Experience operating documented data products • Preferred: Experience using AI agents or agentic workflows • Preferred: Curiosity about emerging data platform technologies • Ability to safely and successfully perform essential job functions consistent with ADA, FMLA, and applicable standards • Ability to maintain regular, punctual attendance • Primarily office and computer-based work with standard engineering and collaboration expectations