About this role
Senior Data Analyst on Arkatechture’s Product team to drive the next generation of data and AI-powered solutions within Arkalytics; operate at the intersection of analytics, AI and engineering to build intelligent data solutions, deploy AI capabilities, and push analytics products using modern AI/BI tooling.
Key Responsibilities
- ['Design, develop, and maintain advanced analytics solutions including predictive models and Generative AI applications', 'Translate business problems into data-driven and AI-enabled solutions', 'End-to-end delivery of analytics and AI initiatives, from data exploration and feature engineering to model development, deployment, and ongoing optimization', 'Operationalize models using robust MLOps practices, including deployment pipelines, automated scoring, version control, and scalable data integrations', 'Collaborate with Product, Engineering, and Services teams to evolve the Analytics Edge and AI roadmap']
Technical Overview
Stack includes SQL, Python, Generative AI, LangChain, LLMs, MLOps, AWS SageMaker, Snowflake, Databricks, BigQuery, Tableau, Power BI; experiences with cloud platforms and Agile environments; focus on end-to-end analytics and AI-enabled product delivery.
Ideal Candidate
The ideal candidate is a senior data analyst with 5+ years of data analytics experience, strong SQL and Python, hands-on ML in production, and experience with Snowflake/Databricks/BigQuery, and proficient in BI tools Tableau or Power BI.
Must-Have Skills
Bachelor’s degree in a relevant field or 5+ years of equivalent practical experience in data scienceanalyticsor applied AIStrong expertise in SQL and Python for data analysismodelingand production workflowsHands-on experience developingdeployingand maintaining machine learning models in production environmentsExperience with MLOps platforms and practicesincluding tools such as AWS SageMaker or similarExperience working with modern data platforms such as Snowflake (preferred)Databricksor BigQueryHands-on experience with Generative AI technologiesincluding LLMsprompt engineeringand frameworks such as LangChainas well as vector databases and related toolingProven experience applying AI and machine learning to real-world business or analytics problems with measurable impactExperience with BI and data visualization tools such as Tableau or Power BIStrong understanding of data warehousingdata modelingand analytics architectureFamiliarity with cloud platformspreferably AWSStrong analytical thinking and problem-solving skills with attention to detailExcellent communication skillswith the ability to convey complex concepts to both technical and non-technical audiencesExperience working in Agile or Scrum environments
Nice-to-Have Skills
Experience building or supporting AI-powered analytics products or featuresExperience with Claude Code or Cortex codeExperience working with financial institutions (credit unionsbanks)Experience on a Product or innovation-focused teamDemonstrated curiosity and passion for emerging AI technologies
Tools & Platforms
Amazon Web ServicesSnowflakeDatabricksBigQueryTableauPower BIAWS SageMakerLangChainLLMsGit
Required Skills
Bachelor’s degree or 5+ years in data science/analytics; SQL; Python; Generative AI; LangChain; LLMs; MLOps; AWS SageMaker; Snowflake; Databricks; BigQuery; Tableau; Power BI; data warehousing; data modeling; analytics architecture; cloud; Agile/Scrum
Hard Skills
SQLPythonGenerative AILangChainLLMsMLOpsAWS SageMakerSnowflakeDatabricksBigQueryTableauPower BIData warehousingData modelingAnalytics architectureCloud platforms (AWS)
Soft Skills
CommunicationTeamworkCollaborationProblem-solvingAttention to detailCuriosity
Keywords for Your Resume
senior data analystremotegenerative aiaimldata analyticsaws sageMakersnowflakedatabricksbigquerytableaupower bipythonsqllangchainllmsagilescrumanalytics platformarkatechtureproduct teamai workflowsGenerative AILangChainLLMsAWS SageMakerSnowflakeDatabricksBigQueryTableauPower BISQL
Deal Breakers
Lack of 5+ years of data analytics / data science experience, No SQL or Python expertise, No experience with ML in production, No exposure to Snowflake/Databricks/BigQuery, No Agile/Scrum experience
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