Analyst​/Junior Developer

Analyst / Junior Developer

Developer I - Software Engineering

The Sr Engineer, Data designs and delivers scalable data architectures and advanced data engineering solutions across on‑premises, cloud, and hybrid platforms to support enterprise analytics and customer intelligence use cases.

• Design and develop advanced data engineering solutions that enable data pipelines, visualization, and analytical tools
• Architect and implement scalable data platforms across on‑premises, cloud, and hybrid environments
• Build, optimize, and operate complex batch and real‑time and near real‑time streaming data pipelines
• Build, optimize, and operate low‑latency, sub‑second APIs on highly scalable, fault‑tolerant architectures
• Design and maintain high‑throughput data pipelines to support agentic AI workloads and real‑time multi‑agent MCP orchestration
• Build and maintain enterprise‑scale Graph Databases that power organizational knowledge graphs and connected data experiences
• Perform data wrangling, exploration, and discovery across heterogeneous data sources to generate insights

• Bachelor's Degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience
• 1-3 years of experience
• Strong experience developing and migrating data solutions across cloud platforms
• Demonstrated technical leadership and mentoring experience
• Strong analytical and problem‑solving skills applied to complex data challenges
• Ability to manage multiple concurrent initiatives with strong organizational and prioritization skills
• Passion for learning and applying new data and platform technologies

• Core Data Engineering & Platforms
• Advanced experience designing and building complex data pipelines using Python and SQL
• Strong experience with cloud platforms and services, including:
  • Azure (Data Factory, Data Lake, Event Hub, Functions, Web Apps, Cosmos DB)
  • Databricks with PySpark, Spark SQL, and Scala Spark, including cluster configuration, autoscaling, and performance optimization (e.g., Photon)
  • Snowflake data warehousing, including schema design (star/snowflake), query optimization, and cost/performance tuning
  • Expertise in SQL, No
    
    SQL, and relational database design and development
• APIs, Streaming & Integration
  • Proficiency designing and consuming RESTful APIs with secure authentication and authorization (OAuth 2.0, JWT, API keys)
  • Experience using Postman and Swagger/OpenAPI for API testing, documentation, and validation
  • Working knowledge of message queuing, stream processing, and highly scalable big‑data data stores
• Engineering Practices
  • Advanced knowledge of data pipeline development using Python and experience with languages such as SQL, DAX, Java, Scala, and/or Go
  • Experience performing root‑cause analysis and using technology to solve complex business problems
  • Experience adopting AI‑assisted development tools and building AI‑powered agents or agentic workflows to automate engineering tasks, accelerate delivery, and enhance data platform capabilities
  • Experience with NL‑to‑SQL query generation using Databricks Genie and Snowflake Cortex to enable natural language access to data assets
  • Hands‑on experience with Unity Catalog for data governance, fine‑grained access control, and end‑to‑end data lineage
  • Experience developing AI‑assisted dbt models, including AI‑generated transformation logic, automated documentation, and intelligent testing
  • Familiarity with AI‑powered data quality tools for automated profiling, anomaly detection, and pipeline observability

• Experience with Iceberg table design and optimization
• Experience with Unity Catalog governance and security
• Cloud platform certifications such as Azure Certified Solutions Architect, Azure Cloud Practitioner, or MCSA
• Experience contributing to enterprise data governance, security, or compliance initiatives
• Experience with ML feature platforms (e.g., Feast, Tecton, or Databricks Feature Store) and vector database engineering (e.g., Pinecone, Weaviate, pgvector)
• Experience designing and operating streaming AI pipelines and applying MLOps practices to data engineering workflows
• Exposure to end‑to‑end ML pipeline ownership and real‑time…