Remote Senior Data Solutions Architect: Spark & Lakehouse

Akkodis; United States; Remote; USD 117,000 - 131,000; Part time

Job summary

Akkodis is seeking a Senior Data Solutions Architect for a 100% remote contract role in the United States. The ideal candidate will have a solid background in Data Architecture, Apache Spark, Databricks, and Lakehouse Architecture and will independently lead complex customer engagements.

Responsibilities include architecting and optimizing large-scale Spark/Databricks workloads, mentoring engineers, and delivering data-driven solutions. Strong communication to business leaders is essential.

Qualifications

• 5–10 years in data engineering or analytics solution delivery.
• 0
• 3+ years hands-on Databricks experience.
• Deep knowledge of Spark internals and PySpark.
• Strong Delta Lake and Structured Streaming knowledge.
• Ability to work autonomously and simplify complex topics.
• Excellent communication to business leaders.

Responsibilities

• Lead engagements from discovery to delivery with ownership.
• Architect and optimize large-scale Spark/Databricks workloads for scalability and cost-efficiency.
• Apply expert Spark skills to troubleshoot and tune distributed data jobs and SQL workloads.
• Design and run PoCs and workshops to demonstrate vision and drive confidence.
• Act as a technical advisor, anticipating issues and delivering data-driven solutions.
• Collaborate with product and engineering teams to improve the customer experience and platform features.
• Mentor junior engineers in PySpark and Lakehouse design.

Skills

Data architecture

Databricks

PySpark

Delta Lake

Tools

Spark Internals

Databricks SQL

Cloud platforms

Job description

Akkodis is seeking a Senior Data Solutions Architect for a 100% remote contract role in the United States. The ideal candidate will have a solid background in Data Architecture, Apache Spark, Databricks, and Lakehouse Architecture and will independently lead complex customer engagements.

Responsibilities include architecting and optimizing large-scale Spark/Databricks workloads, mentoring engineers, and delivering data-driven solutions. Strong communication to business leaders is essential.