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Koantek

Senior Solution Architect- Spark & Databricks Expert

Reposted One Month Ago
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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