Senior Data Engineer
Evolution Cloud Services (EVOCS)
| Company | Evolution Cloud Services (EVOCS) |
| Category | Engineering |
| Location | United States |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 4 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
EVOCS OVERVIEW
EVOCS’s journey began with a mission to empower businesses with advisory expertise, empowered with idealtechnologies to provide them with comprehensive solutions to grow and prosper.
Founded by a team of passionate experts, EVOCS has grown into a trusted partner to a growing number of leaders across their respective industries. Our roots in employee-managed operations reflect our commitment to quality, consistency, and client success.
If you enjoy working in a hyper-fast-growing company, are eager to be part of an agile team, and want to be part of our success story, then let’s talk! 🎯 Role Overview
As a Senior Data Engineer , you will play a critical role in designing, building, and maintaining the data infrastructure that powers analytics solutions across a variety of enterprise client environments.
This role combines modern data engineering practices with strong database and data quality fundamentals. You will be responsible for building scalable ETL/ELT pipelines, designing robust data models, integrating data from diverse platforms, and ensuring that every engagement is supported by a reliable, well-documented data foundation.
You'll work primarily within Microsoft Fabric environments while collaborating closely with analytics, engineering, and client stakeholders to deliver high-quality, production-ready data solutions.
We are looking for someone who takes ownership of data quality, enjoys solving complex integration challenges, and thrives in client-facing consulting environments where every engagement presents a unique set of technical challenges.
🧩 What you will do
In this role, you will:
Design, build, and maintain ETL/ELT pipelines for enterprise data ingestion and transformation across multiple client environments.
Develop and maintain SQL views, schemas, and transformation logic that serve as the foundation for Power BI and other analytics solutions.
Profile source data before development begins, identifying data quality issues, anomalies, duplicates, null values, and integrity concerns.
Produce and maintain comprehensive data dictionaries, lineage documentation, and transformation documentation for every engagement.
Build and manage data pipelines primarily within Microsoft Fabric while supporting Databricks and other client-specific environments as needed.
Integrate data from REST APIs, GraphQL endpoints, and webhook-based sources, implementing authentication, pagination, rate-limiting, and error handling.
Implement monitoring, alerting, and refresh processes to proactively identify and resolve pipeline failures.
Validate data integrity throughout development to ensure reliable and accurate downstream analytics.
Translate client business requirements into scalable technical data models while identifying limitations and gaps within source systems.
Collaborate closely with visualization developers to ensure the data layer supports reporting and analytics requirements.
Create and maintain clear handoff documentation, architecture documentation, and operational runbooks.
Mentor junior engineers and contribute to engineering best practices, documentation standards, and delivery excellence.
Participate in engagement planning, solution design, and project execution from kickoff through delivery.
🧠 What you will bring
We’re looking for someone who has:
8+ years of professional experience in Data Engineering, Backend Platform Engineering, or large-scale data infrastructure.
3+ years of experience in client-facing or consulting-focused data engineering environments.
Advanced SQL expertise, including schema design, query optimization, complex views, CTEs, window functions, deduplication strategies, and data modeling.
Strong Python experience for ETL development, automation, PySpark, and data processing workflows.
Hands-on experience building and maintaining enterprise-scale ETL/ELT pipelines in production environments.
Exper
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