Senior Data Architect

Hi,DATAECONOMY is one of the fastest-growing Data & Analytics company with global presence. We are well-differentiated and are known for our Thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.Sr./ Lead Data Engineer – DatabricksRaleigh, NC/ New JerseyFull-timeKey ResponsibilitiesData Engineering & PipelinesBuild scalable, production-grade ETL/ELT pipelines using Databricks (PySpark, Spark SQL, Delta Live Tables, Workflows).Ingest structured, semi-structured, and streaming data into Bronze, Silver, and Gold layers.Develop optimized transformations, data quality rules, and reusable framework components.Implement best practices for job orchestration, monitoring, alerting, and automation.Hands-on experience: Spark, Delta Lake, Workflows, Unity Catalog.Strong SQL programming and performance tuning skills.Experience with cloud environments (AWS/Azure/GCP).Experience with modern data lakehouse concepts and distributed systems.Strong understanding of Lakeflow Connect, LSDP/Lakehouse, Medallion Architecture, Data Validations, Genie, and Agent Bricks/RAG use cases.Should be able to explain these concepts using real project examples and architecture decisions.Data ModelingDesign and implement dimensional models (star/snowflake) for analytical workloads.Apply normalization/denormalization strategies for performance and usability.Create physical data models aligned to Delta Lake and Medallion architecture.Ensure data quality, integrity, and alignment with enterprise governance policies.Technology StackAdvanced hands-on Databricks experience: Spark, Delta Lake, Workflows, Unity Catalog.Strong SQL/Python programming and performance tuning skills.Experience with cloud environments (AWS/Azure/GCP).Experience with modern data lakehouse concepts and distributed systems.Required Qualifications7–10+ years of experience in data engineering.Proven experience building and deploying large-scale Databricks pipelines.Strong understanding of Medallion architecture (Bronze/Silver/Gold).Proficiency with PySpark, SQL, ETL/ELT frameworks, and Delta Lake optimizations.Strong experience working with CI/CD, Git, and job orchestration tools.Deep understanding of data modeling principles for warehousing and analytics.Preferred SkillsKnowledge of data governance, metadata management, and Unity Catalog.Experience with streaming technologies (Auto-Loader, Structured Streaming).Background in data security, compliance, and access models.Knowledge of performance tuning and cost optimization in cloud environments.Experience with tools like Airflow, Databricks Workflows, dbt, or similar.