Databricks Architect

Job description

Role: Senior Principal Consultant (Databricks Architect)

In this role, the Databricks Architect is responsible for providing technical direction and lead a group of one or more developer to address a goal.

Responsibilities

• Architect and design solutions to meet functional and non-functional requirements.
• Create and review architecture and solution design artifacts.
• Evangelize re-use through the implementation of shared assets.
• Enforce adherence to architectural standards/principles, global product-specific guidelines, usability design standards, etc.
• Proactively guide engineering methodologies, standards, and leading practices.
• Guidance of engineering staff and reviews of as-built configurations during the construction phase.
• Provide insight and direction on roles and responsibilities required for solution operations.
• Identify, communicate and mitigate Risks, Assumptions, Issues, and Decisions throughout the full lifecycle.
• Considers the art of the possible, compares various architectural options based on feasibility and impact, and proposes actionable plans.
• Demonstrate strong analytical and technical problem-solving skills.
• Ability to analyze and operate at various levels of abstraction.
• Ability to balance what is strategically right with what is practically realistic.
• Growing the Data Engineering business by helping customers identify opportunities to deliver improved business outcomes, designing and driving the implementation of those solutions.
• Growing & retaining the Data Engineering team with appropriate skills and experience to deliver high quality services to our customers.
• Supporting and developing our people, including learning & development, certification & career development plans
• Providing technical governance and oversight for solution design and implementation
• Should have technical foresight to understand new technology and advancement.
• Leading team in the definition of best practices & repeatable methodologies in Cloud Data Engineering, including Data Storage, ETL, Data Integration & Migration, Data Warehousing and Data Governance
• Should have Technical Experience in Azure, AWS & GCP Cloud Data Engineering services and solutions.
• Contributing to Sales & Pre-sales activities including proposals, pursuits, demonstrations, and proof of concept initiatives
• Evangelizing the Data Engineering service offerings to both internal and external stakeholders
• Development of Whitepapers, blogs, webinars and other though leadership material
• Development of Go-to-Market and Service Offering definitions for Data Engineering
• Working with Learning & Development teams to establish appropriate learning & certification paths for their domain.
• Expand the business within existing accounts and help clients, by building and sustaining strategic executive relationships, doubling up as their trusted business technology advisor.
• Position differentiated and custom solutions to clients, based on the market trends, specific needs of the clients and the supporting business cases.
• Build new Data capabilities, solutions, assets, accelerators, and team competencies.
• Manage multiple opportunities through the entire business cycle simultaneously, working with cross-functional teams as necessary.

Qualifications we seek in you

Minimum qualifications

• Excellent technical architecture skills, enabling the creation of future-proof, complex global solutions.
• Excellent interpersonal communication and organizational skills are required to operate as a leading member of global, distributed teams that deliver quality services and solutions.
• Ability to rapidly gain knowledge of the organizational structure of the firm to facilitate work with groups outside of the immediate technical team.
• Knowledge and experience in IT methodologies and life cycles that will be used.
• Familiar with solution implementation/management, service/operations management, etc.
• Leadership skills can inspire others and persuade.
• Maintains close awareness of new and emerging technologies and their potential application for service offerings and products.
• Bachelor's Degree or equivalency (CS, CE, CIS, IS, MIS, or engineering discipline) or equivalent work experience
• Experience in a solution architecture role using service and hosting solutions such as private/public cloud IaaS, PaaS, and SaaS platforms.
• Experience in architecting and designing technical solutions for cloud-centric solutions based on industry standards using IaaS, PaaS, and SaaS capabilities.
• Must have strong hands-on experience on various cloud services like ADF/Lambda, ADLS/S3, Security, Monitoring, Governance
• Must have experience to design platform on Databricks.
• 3+ years of hands-on Experience to design and build Databricks based solution on any cloud platform.
• 1+ year of hands-on experience to design and build solution powered by DBT models and integrate with databricks.
• Must be very good designing End-to-End solution on cloud platform.
• Must have good knowledge of Data Engineering concept and related services of cloud.
• Must have good experience in Python and Spark.
• Must have good experience in setting up development best practices.
• Intermediate level knowledge is required for Data Modelling.
• Good to have knowledge of docker and Kubernetes.
• Experience with claims-based authentication (SAML/OAuth/OIDC), MFA, RBAC, SSO etc.
• Knowledge of cloud security controls including tenant isolation, encryption at rest, encryption in transit, key management, vulnerability assessments, application firewalls, SIEM, etc.
• Experience building and supporting mission-critical technology components with DR capabilities.
• Experience with multi-tier system and service design and development for large enterprises
• Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technologies.
• Exposure to infrastructure and application security technologies and approaches
• Familiarity with requirements gathering techniques.

Preferred qualifications

• Must have designed the E2E architecture of unified data platform covering all the aspect of data lifecycle starting from Data Ingestion, Transformation, Serve and consumption.
• Must have excellent coding skills either Python or Scala, preferably Python.
• Must have at least 10+ years of experience in Data Engineering domain with total of 12+ years.
• Must have designed and implemented at least 2-3 project end-to-end in Databricks.
• Must have at least 3+ years of experience on databricks which consists of various components as below
• Delta lake
• dbConnect
• db API 2.0
• SQL Endpoint – Photon engine
• Unity Catalog
• Databricks workflows orchestration
• Security management
• Platform governance
• Data Security
• Must have knowledge of new features available in Databricks and its implications along with various possible use-case.
• Must have followed various architectural principles to design best suited per problem.
• Must be well versed with Databricks Lakehouse concept and its implementation in enterprise environments.
• Must have strong understanding of Data warehousing and various governance and security standards around Databricks.
• Must have knowledge of cluster optimization and its integration with various cloud services.
• Must have good understanding to create complex data pipeline.
• Must be strong in SQL and sprak-sql.
• Must have strong performance optimization skills to improve efficiency and reduce cost.
• Must have worked on designing both Batch and streaming data pipeline.
• Must have extensive knowledge of Spark and Hive data processing framework.
• Must have worked on any cloud (Azure, AWS, GCP) and most common services like ADLS/S3, ADF/Lambda, CosmosDB/DynamoDB, ASB/SQS, Cloud databases.
• Must be strong in writing unit test case and integration test.
• Must have strong communication skills and have worked with cross platform team.
• Must have great attitude towards learning new skills and upskilling the existing skills.
• Responsible to set best practices around Databricks CI/CD.
• Must understand composable architecture to take fullest advantage of Databricks capabilities.
• Good to have Rest API knowledge.
• Good to have understanding around cost distribution.
• Good to have if worked on migration project to build Unified data platform.
• Good to have knowledge of DBT.
• Experience around DevSecOps including docker and Kubernetes.
• Software development full lifecycle methodologies, patterns, frameworks, libraries, and tools
• Knowledge of programming and scripting languages such as JavaScript, PowerShell, Bash, SQL, Java, Python, etc.
• Experience with data ingestion technologies such as Azure Data Factory, SSIS, Pentaho, Alteryx
• Experience with visualization tools such as Tableau, Power BI
• Experience with machine learning tools such as mlFlow, Databricks AI/ML, Azure ML, AWS sagemaker, etc.
• Experience in distilling complex technical challenges to actionable decisions for stakeholders and guiding project teams by building consensus and mediating compromises when necessary.
• Experience coordinating the intersection of complex system dependencies and interactions
• Experience in solution delivery using common methodologies especially SAFe Agile but also Waterfall, Iterative, etc.

Demonstrated knowledge of relevant industry trends and standards