Platform Engineer - DevOps (contract)
Role summary
Seeking a contract Platform Engineer with a strong Data Engineering focus for a granular load forecasting initiative. This role involves building and maintaining data infrastructure and pipelines, particularly for non-standard data sources. Responsibilities include designing and developing ETL/ELT pipelines in Databricks, managing data ingestion, ensuring data quality, and contributing to infrastructure automation. The ideal candidate will have 5-7 years of experience in Data Engineering, Platform Engineering, or DevOps, with proficiency in Python, SQL, Databricks, Git, and CI/CD. This is a collaborative role requiring strong communication and stakeholder management skills to bridge business and technical teams.
Position Overview
We are seeking a
Platform Engineer with a strong Data Engineering focus
to support a large-scale
granular load forecasting initiative
. This role will be instrumental in building and maintaining the
data infrastructure and pipelines
that power forecasting and analytics across the organization.
You will work within a highly collaborative environment, partnering with
IT, data analysts, and business stakeholders
to enable reliable, scalable data ingestion and processing—particularly from
non-standard and non-API sources
.
This role combines
hands-on engineering
,
cross-team coordination
, and
platform ownership
, with a strong emphasis on
Databricks and ETL pipeline development
.
Key Responsibilities
- Design, build, and maintain data pipelines and ingestion frameworks in Databricks
- Develop and manage ETL/ELT workflows to support forecasting datasets
- Work with cross-functional teams to ingest non-standard data sources (e.g., reports, manual data inputs, legacy systems)
- Partner with IT to ensure alignment with data governance, security, and platform standards
- Serve as a technical liaison between engineering, IT, and business teams
- Support data discovery efforts by translating business inputs into structured pipeline requirements
- Perform data cleanup, validation, and quality assurance to ensure integrity of forecasting data
- Manage code deployment, version control (Git), and Databricks asset bundles (DBX)
- Monitor and troubleshoot pipelines and platform performance across dev, test, and production environments
- Contribute to infrastructure automation, deployment pipelines, and platform optimization (cloud/on-prem hybrid)
Required Qualifications
- 5–7 years of experience in Data Engineering, Platform Engineering, or DevOps
- Strong hands-on experience with Databricks (core platform focus)
- Proven experience building ETL/ELT pipelines and data workflows
- Proficiency in Python and SQL
- Experience working with data ingestion from non-standard or legacy sources
- Strong understanding of data quality, validation, and cleanup processes
- Experience with Git, CI/CD, and deployment pipelines
- Solid knowledge of enterprise data architecture, scalability, and security principles
- Excellent communication and stakeholder management skills
Preferred Qualifications
- Experience supporting data migration or conversion efforts (e.g., SAP IS-U or similar systems)
- Familiarity with data governance and metadata management frameworks
- Exposure to integration patterns (API, batch, middleware platforms)
- Experience working with data validation and profiling tools
- Basic exposure to ML pipeline development (not a primary focus)
- Experience in utility, energy, or forecasting domains (nice to have)
Key Skills & Competencies
- Databricks Expertise – primary platform ownership and development
- Data Pipeline Development – strong foundational engineering skills
- Data Integration – especially across ambiguous or non-technical sources
- Critical Thinking – ability to operate in ambiguous, discovery-heavy environments
- Collaboration & Communication – working across IT and business teams
- Problem Solving – troubleshooting across data and platform layers
What Success Looks Like
- You can take loosely defined data inputs and turn them into structured, reliable pipelines
- You effectively bridge the gap between business users and technical systems
- You ensure data entering the platform is accurate, validated, and usable for forecasting
- You become a trusted partner to IT and analytics teams in a high-visibility capital project
Interview Process
- Single-round panel interview (2–3 interviewers)
- Focus on technical depth, real-world pipeline experience, and stakeholder collaboration
Nice-to-Know Context
- This is part of a large capital project with high visibility
- The environment is highly collaborative and less rigid than traditional IT structures
- Strong emphasis on coordination, communication, and practical engineering execution
Pay Rate Range
46 - 61 USD hourly