Resident Solutions Architect - Spark & Databricks Expert

 Posted 2 months ago
     
5-10 years experience
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AI Summary

Lead customer engagements from discovery to delivery, ensuring full ownership and accountability. Architect and optimize large-scale Spark/Databricks workloads while collaborating with cross-functional teams.

This is a remote position.

Role: Senior Resident Solutions Architect (RSA) – Spark Expert

Experience: 5 – 10+ Years
Location: Remote
Employment Type: Full-time

Role Overview

We are seeking a Senior Data Solutions Consultant with deep expertise in Apache Spark and Databricks. This role requires a decisive, agentic-forward approach to problem-solving. You will independently lead complex customer engagements, bridging hands-on data engineering excellence with strategic technical leadership. As a trusted advisor, you will proactively build and implement solutions that unlock significant value for our customers.

Key Responsibilities

  • Customer Leadership: Lead engagements from discovery to delivery with full ownership and accountability.

  • Architecture & Optimization: Architect, implement, and optimize large-scale Spark/Databricks workloads focusing on scalability and cost-efficiency.

  • Spark Expertise: Apply expert-level Spark fundamentals to troubleshoot and tune distributed data jobs and SQL workloads.

  • Proactive Delivery: Design and execute PoCs and workshops to demonstrate solution vision and inspire customer confidence.

  • Strategic Advocacy: Act as a technical advocate for customers, anticipating issues and applying creative, data-driven solutions.

  • Cross-functional Partnership: Collaborate with product and engineering teams to improve customer experience and platform features.

  • Mentorship: Champion best practices in PySpark, Databricks, and Lakehouse design while mentoring junior engineers.

Required Qualifications

  • Experience: 5–10 years in data engineering or analytics solution delivery.

  • Databricks Mastery: 3+ years of hands-on expertise, including job optimization, debugging, and workload governance.

  • Technical Depth: Deep understanding of Spark Internals, PySpark, and Databricks SQL (DBSQL) performance tuning.

  • Modern Lakehouse: Strong knowledge of Delta Lake, Structured Streaming, and cloud infrastructure.

  • Autonomy: Proven ability to identify and solve complex technical problems with minimal oversight.

  • Communication: Exceptional skills to simplify technical complexity for business leaders.

Preferred Qualifications

  • Certifications: Databricks Certified Data Engineer Professional.

  • Advanced Skills: Experience with Delta Live Tables (DLT) and Unity Catalog (UC).

  • Consulting Background: Experience in large-scale data migration or AI-assisted analytics in enterprise environments.



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