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Koantek

Senior Solution Architect- Spark & Databricks Expert

Reposted Yesterday
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
Lead customer engagements to architect, implement, and optimize large-scale Spark and Databricks workloads. Troubleshoot and tune distributed PySpark and DBSQL jobs, design PoCs/workshops, advocate technical solutions, mentor junior engineers, and collaborate cross-functionally to improve platform features and cost-efficiency.
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Role: Senior Solution Architect– 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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