Koantek

Role Description We are seeking an elite Senior Solutions Architect with deep expertise in enterprise data architecture and cloud modernization. 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 architectures that safely migrate legacy healthcare estates into modern cloud Lakehouses. Key Responsibilities - Customer Leadership: Lead engagements from discovery to delivery with full ownership and accountability for enterprise healthcare accounts. - Architecture & Migration: Architect and execute the decommissioning of legacy Teradata environments, shifting workloads into highly scalable Databricks structures. - Infrastructure as Code: Design and build automated, reproducible cloud environments using Terraform to manage workspaces and networking. - Spark & Optimization: Apply expert-level Spark fundamentals and Spark internals knowledge to troubleshoot, tune, and optimize large-scale distributed workloads and SQL jobs. - Healthcare Governance: Implement strict data security models complying with HIPAA and PHI regulations using Unity Catalog for fine-grained access control. - Proactive Delivery: Design and execute PoCs and architecture workshops to demonstrate solution vision and inspire customer confidence. - Mentorship: Champion best practices in PySpark, Delta Lake, and Lakehouse design while mentoring engineering teams. Qualifications - 15+ years of dedicated experience in data engineering, enterprise architecture, and major cloud migrations. - Deep, hands-on history migrating legacy Teradata estates, BTEQ scripts, and enterprise warehouses. - 4+ years of hands-on expertise including job optimization, debugging, and workload governance in Databricks. - Deep understanding of Spark Internals, PySpark, Databricks SQL (DBSQL) performance tuning, and Delta Lake. - Proven experience using Terraform to provision and manage cloud infrastructure in highly regulated environments. - Solid understanding of patient data complexities, data models, and strict compliance (HIPAA/PHI) guardrails. - Proven ability to identify and solve complex technical problems with minimal oversight. Preferred Qualifications - Databricks Certified Data Engineer Professional or Databricks Certified Solutions Architect. - Full-scale enterprise implementation experience with Delta Live Tables (DLT) and Unity Catalog (UC). - Experience in large-scale data migration or production technical consulting for enterprise clients.

Role Description We are seeking an experienced and dedicated Senior Solutions Architect to lead technical engagements and provide strategic guidance for our strategic client accounts. This high-impact role requires deep expertise in the Databricks Platform, acting as the client's primary technical advisor for complex data, analytics, and AI initiatives. You will bridge business objectives with technical execution, designing and delivering scalable Lakehouse architectures while mentoring client teams and driving adoption of advanced Databricks capabilities. Key Responsibilities - Platform Architecture & Design: Lead the design and implementation of enterprise-scale, secure, and high-performance data architectures on the Databricks Lakehouse Platform, leveraging Delta Lake, Unity Catalog, serverless compute, and advanced features like Photon engine. - Hands-On Implementation & Leadership: Provide expert hands-on guidance and lead development of complex data engineering pipelines using Apache Spark, PySpark, SQL, and Scala, with a focus on code quality, optimization, and best practices. - Performance Tuning & Optimization: Identify, diagnose, and resolve complex performance issues in large-scale data processing, query optimization, and cluster configurations. - Client Advisory & Strategy: Serve as the trusted senior technical advisor to client leadership, engineering, and data science teams, delivering best practices in data governance, security, MLOps, and operational excellence. - Knowledge Transfer & Team Enablement: Design and deliver advanced workshops, training sessions, and ongoing mentorship to accelerate client team proficiency and self-sufficiency. - Feature Adoption & Innovation: Champion the adoption of new Databricks features and tools (e.g., Photon, AI/BI, Mosaic AI) and integrate them effectively into client environments. - Cloud Integration: Ensure seamless, optimized, and secure integration with major cloud platforms (AWS, Azure, GCP) including storage, networking, IAM, and security services. Qualifications - 8+ years of experience in data engineering, big data architecture, or software engineering with a focus on data platforms. - 5+ years of deep, hands-on experience designing, implementing, and optimizing solutions on the Databricks platform. - Expert-level proficiency in Apache Spark ecosystem (PySpark, Spark SQL, Scala) and large-scale data processing. - Strong experience with cloud infrastructure (AWS, Azure, GCP), including storage solutions (S3, ADLS), networking, and security models. - Deep expertise in Databricks Lakehouse architecture, Delta Lake, Unity Catalog, and best practices for ETL/ELT, data governance, and reliability. - Proficiency in Python, Scala, advanced SQL, and modern DevOps practices including Docker, Kubernetes, and CI/CD. - Exceptional client-facing and presentation skills, able to communicate complex concepts to both technical and C-level audiences. - Proven leadership in client engagements, ability to drive consensus and influence decision-making across stakeholder groups. - Strong problem-solving, analytical skills, and a proactive, consultative mindset. Preferred Qualifications - Databricks Certified Professional or higher certifications. - Relevant cloud certifications (e.g., AWS Certified Big Data, Azure Data Engineer, Google Professional Data Engineer). - Experience with MLOps, generative AI, and advanced analytics on Databricks. - Prior experience in senior consulting, solution architecture, or resident roles. Company Description Koantek is a Databricks-exclusive system integrator trusted by enterprises to move from platform adoption to real AI impact. A seven-time Databricks Partner of the Year, we’re recognized with Brickbuilder Specializations across AI, Security & Governance, Migrations, Lakeflow, and multiple industries. We combine deep technical expertise with proven delivery to help customers operationalize data and AI at scale — securely, efficiently, and with measurable business outcomes.

Role Description We are seeking an experienced, highly technical Senior AI Engineer / Data Scientist to join our customer-facing consulting team. This remote role requires a unique blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. You will design, deploy, and maintain production-grade ML solutions, including advanced Generative AI and NLP models, for our diverse client base. Key Responsibilities: - Technical Consulting: Lead end-to-end ML implementations directly with clients, translating business problems into robust technical solutions. - MLOps and Pipelines: Design, build, and maintain production-grade ML pipelines with a strong focus on CI/CD, automation, and scalability. - GenAI and NLP Deployment: Implement and optimize cutting-edge Generative AI applications (such as LLMs and RAG) in live production settings. - Infrastructure and Data Scale: Manage underlying infrastructure using Docker, pipeline orchestrators, and distributed computing frameworks like Apache Spark. - Stakeholder Management: Clearly communicate technical findings, proposals, and project status to both technical and non-technical audiences. Qualifications - 4+ years of professional experience developing, deploying, and maintaining ML models in a live production environment (Mandatory). - 3+ years of experience in a customer-facing consulting or Solutions Architect role. - Strong expertise in the MLOps lifecycle (model versioning, testing, monitoring, and automated deployment). - Solid hands-on experience with containerization (Docker) and data pipeline orchestration. - Proven track record of deploying Generative AI and NLP solutions for client applications. - Excellent verbal and written communication skills. Requirements - Hands-on experience with modern ML platform stacks, specifically Databricks MLOps Stacks. - Deep knowledge of large-scale data processing and distributed machine learning techniques. - A strong commitment to continuous learning in emerging ML fields and GenAI application architectures.

• Analyze Databricks job roles and propose qualified consultants • Build and serve as primary point of contact for Databricks counterparts • Monitor and maintain peak utilization rates • Manage all resource allocations, project updates, and consultant profiles within Salesforce • Generate and present data-driven reports • Collaborate with Finance, Recruitment, and Delivery teams

Role Description We are seeking an accomplished, technology-driven Lead Data Platform Architect / Migration Specialist to spearhead the modernization of our core enterprise financial and tax allocation engines. In this role, you will lead the architectural design, definition of migration strategies, and hands-on implementation to transition large-scale legacy relational database systems (SQL Server/T-SQL) into a modern, cloud-native Databricks Lakehouse platform. The ideal candidate will have extensive experience in high-throughput distributed systems, Databricks compute optimization, performance tuning, and complex pipeline orchestration. Key Responsibilities - Architecture & Strategy: Validate, refine, and own the target architecture on Databricks. Define robust migration strategies and production-ready reference patterns to convert 150+ complex stored procedures into PySpark and Structured/Declarative Pipelines (SDP). - Pipeline Engineering: Design distributed processing frameworks, control flows, and configuration-driven parameter handling for both full and incremental recalculation modes. - Performance Optimization: Address performance deltas between small and large workloads. Architect and implement acceleration techniques such as caching, partition pruning, cluster sizing, and offline/pre-calculation strategies to maintain sub-30-second user-facing reporting SLAs. - Orchestration & Observability: Design and deploy enterprise-level pipeline orchestration using tools like Apache Airflow or Databricks Workflows. Integrate robust logging, error handling, and observability patterns into existing enterprise monitoring frameworks. - Governance & Security: Implement data governance models, data lineage, and schema evolution utilizing tools like Unity Catalog. - AI-Assisted Delivery & Code Quality: Establish best practices for AI-assisted code generation (e.g., using Claude or advanced LLMs), providing code-review patterns and refactoring frameworks to ensure maintainable and performant output. - Team Enablement: Lead code walkthroughs, design reviews, and pair-programming sessions with the development team to accelerate knowledge transfer and technical excellence. Qualifications - Deep expert-level knowledge of Databricks (Lakehouse architecture, Delta Lake, Unity Catalog) and Apache Spark / PySpark. - Strong background in relational databases, with advanced proficiency in SQL Server, T-SQL, and Stored Procedures. - Ability to reverse-engineer and refactor legacy database logic into distributed paradigms. - Hands-on experience with Apache Airflow or similar modern workflow orchestrators. - Proven track record in cost optimization (FinOps), cluster tuning, autoscaling configurations, and handling skewed data profiles. - Experience with Infrastructure as Code (Terraform), data build tool (dbt), testing frameworks (PyTest), and automated Git-based workflows. - 10+ years of experience in Data Engineering/Architecture, with at least 3+ years specifically leading large-scale cloud data migrations. - Bachelor’s or Master's degree in Computer Science, Engineering, or a related technical field. Preferred Certifications - Databricks Certified Data Engineer Associate / Professional - Databricks Certified Solutions Architect - AWS Certified Database Specialist or equivalent Cloud Certifications

Role Description 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. Qualifications - 5–10 years in data engineering or analytics solution delivery. - 3+ years of hands-on expertise in Databricks, including job optimization, debugging, and workload governance. - Deep understanding of Spark Internals, PySpark, and Databricks SQL (DBSQL) performance tuning. - Strong knowledge of Delta Lake, Structured Streaming, and cloud infrastructure. - Proven ability to identify and solve complex technical problems with minimal oversight. - Exceptional skills to simplify technical complexity for business leaders. Preferred Qualifications - Databricks Certified Data Engineer Professional. - Experience with Delta Live Tables (DLT) and Unity Catalog (UC). - Experience in large-scale data migration or AI-assisted analytics in enterprise environments.

Role Description 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. Qualifications - 5–10 years in data engineering or analytics solution delivery. - 3+ years of hands-on expertise in Databricks, including job optimization, debugging, and workload governance. - Deep understanding of Spark Internals, PySpark, and Databricks SQL (DBSQL) performance tuning. - Strong knowledge of Delta Lake, Structured Streaming, and cloud infrastructure. - Proven ability to identify and solve complex technical problems with minimal oversight. - Exceptional skills to simplify technical complexity for business leaders. Preferred Qualifications - Databricks Certified Data Engineer Professional. - Experience with Delta Live Tables (DLT) and Unity Catalog (UC). - Experience in large-scale data migration or AI-assisted analytics in enterprise environments.

• Lead engagements from discovery to delivery with full ownership and accountability. • Architect, implement, and optimize large-scale Spark/Databricks workloads focusing on scalability and cost-efficiency. • Apply expert-level Spark fundamentals to troubleshoot and tune distributed data jobs and SQL workloads. • Design and execute PoCs and workshops to demonstrate solution vision and inspire customer confidence. • Act as a technical advocate for customers, anticipating issues and applying creative, data-driven solutions. • Collaborate with product and engineering teams to improve customer experience and platform features. • Champion best practices in PySpark, Databricks, and Lakehouse design while mentoring junior engineers.

Role Description 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. Qualifications - 5–10 years in data engineering or analytics solution delivery. - 3+ years of hands-on expertise in Databricks, including job optimization, debugging, and workload governance. - Deep understanding of Spark Internals, PySpark, and Databricks SQL (DBSQL) performance tuning. - Strong knowledge of Delta Lake, Structured Streaming, and cloud infrastructure. - Proven ability to identify and solve complex technical problems with minimal oversight. - Exceptional skills to simplify technical complexity for business leaders. Preferred Qualifications - Databricks Certified Data Engineer Professional. - Experience with Delta Live Tables (DLT) and Unity Catalog (UC). - Experience in large-scale data migration or AI-assisted analytics in enterprise environments.

• Lead engagements from discovery to delivery with full ownership • Architect and optimize large-scale Spark/Databricks workloads • Troubleshoot and tune distributed data jobs and SQL workloads • Design and execute PoCs and workshops • Act as a technical advocate for customers • Collaborate with product and engineering teams • Champion best practices in PySpark and Databricks while mentoring junior engineers.