Gotham Technology Group
Senior Global Data Warehouse Architect
Gotham Technology Group, New York, New York, us, 10261
Senior Global Data Warehouse Architect
Job Title:
Senior Global Data Warehouse Architect
Location:
Hybrid in New York, NY (Onsite 3 days/week)
Duration:
Full-Time/Permanent
Position Summary We are seeking a Senior Global Data Warehouse Architect to design and deliver modern, scalable, and high-performing data platforms that enable advanced financial and operational analytics. The role focuses on defining enterprise data architecture strategy, optimizing data flows, and ensuring data structures are reliable, efficient, and built for analytical depth and scalability.
The architect will develop data platforms that deliver reconciled financial and operational metrics, reduce time-to-insight, and establish standards for data governance, lineage, and model reusability to elevate data quality across the enterprise.
Responsibilities
Design and implement enterprise-grade data architectures on Databricks, Snowflake, or similar platforms for real-time and batch analytical workloads.
Build efficient ELT/ETL workflows using Spark, Python, and SQL to ingest, transform, and curate large volumes of structured and unstructured financial and operational data.
Create and maintain dimensional, normalized, and semantic data models to support financial reporting, performance analytics, and forecasting.
Lead integration design for financial and HRIS systems, ensuring accurate reconciliation and alignment with enterprise data warehouse schemas.
Enforce data governance policies, lineage tracking, and metadata standards to ensure data accuracy, consistency, and regulatory compliance.
Tune query performance, optimize compute and storage costs, and implement data caching and partitioning strategies to improve processing speed and efficiency.
Collaborate with data engineers, BI developers, finance analysts, and technology teams to translate business requirements into scalable data solutions.
Evaluate new tools, frameworks, and architectures to enhance data platform performance and scalability.
Qualifications
8+ years of experience in data architecture, data engineering, or BI engineering roles.
Hands-on experience architecting solutions on Databricks and/or Snowflake.
Strong proficiency in SQL, Python, and Spark.
Deep understanding of data modeling principles (3NF, star/snowflake schemas, data vault).
Proven experience designing data lakes and lakehouse architectures.
Familiarity with financial data structures, accounting schemas, and practice management systems such as Elite 3E or Aderant.
Experience supporting financial planning, billing, profitability, and time & expense analytics.
Experience with cloud platforms (AWS, Azure, or GCP), data platform tools (Databricks, Snowflake, S3, Delta Lake), and BI/visualization tools (Power BI, Tableau, or equivalent).
Strong analytical, problem-solving, and communication skills.
Ability to influence and align technical direction across teams.
Relevant certifications preferred: Databricks Certified Data Engineer/Architect, Snowflake SnowPro Advanced: Architect, TOGAF or other enterprise data architecture credentials.
Seniority level Mid-Senior level
Employment type Full-time
Job function Information Technology
Industries IT Services and IT Consulting
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Senior Global Data Warehouse Architect
Location:
Hybrid in New York, NY (Onsite 3 days/week)
Duration:
Full-Time/Permanent
Position Summary We are seeking a Senior Global Data Warehouse Architect to design and deliver modern, scalable, and high-performing data platforms that enable advanced financial and operational analytics. The role focuses on defining enterprise data architecture strategy, optimizing data flows, and ensuring data structures are reliable, efficient, and built for analytical depth and scalability.
The architect will develop data platforms that deliver reconciled financial and operational metrics, reduce time-to-insight, and establish standards for data governance, lineage, and model reusability to elevate data quality across the enterprise.
Responsibilities
Design and implement enterprise-grade data architectures on Databricks, Snowflake, or similar platforms for real-time and batch analytical workloads.
Build efficient ELT/ETL workflows using Spark, Python, and SQL to ingest, transform, and curate large volumes of structured and unstructured financial and operational data.
Create and maintain dimensional, normalized, and semantic data models to support financial reporting, performance analytics, and forecasting.
Lead integration design for financial and HRIS systems, ensuring accurate reconciliation and alignment with enterprise data warehouse schemas.
Enforce data governance policies, lineage tracking, and metadata standards to ensure data accuracy, consistency, and regulatory compliance.
Tune query performance, optimize compute and storage costs, and implement data caching and partitioning strategies to improve processing speed and efficiency.
Collaborate with data engineers, BI developers, finance analysts, and technology teams to translate business requirements into scalable data solutions.
Evaluate new tools, frameworks, and architectures to enhance data platform performance and scalability.
Qualifications
8+ years of experience in data architecture, data engineering, or BI engineering roles.
Hands-on experience architecting solutions on Databricks and/or Snowflake.
Strong proficiency in SQL, Python, and Spark.
Deep understanding of data modeling principles (3NF, star/snowflake schemas, data vault).
Proven experience designing data lakes and lakehouse architectures.
Familiarity with financial data structures, accounting schemas, and practice management systems such as Elite 3E or Aderant.
Experience supporting financial planning, billing, profitability, and time & expense analytics.
Experience with cloud platforms (AWS, Azure, or GCP), data platform tools (Databricks, Snowflake, S3, Delta Lake), and BI/visualization tools (Power BI, Tableau, or equivalent).
Strong analytical, problem-solving, and communication skills.
Ability to influence and align technical direction across teams.
Relevant certifications preferred: Databricks Certified Data Engineer/Architect, Snowflake SnowPro Advanced: Architect, TOGAF or other enterprise data architecture credentials.
Seniority level Mid-Senior level
Employment type Full-time
Job function Information Technology
Industries IT Services and IT Consulting
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