Drive impactful data architecture strategies to enhance analytics capabilities. Collaborate with cross-functional teams for scalable data solutions. Competitive compensation and professional development opportunities in a hybrid work environment.
Global Data Architect
in Information Technology PermanentJob Detail
Job Description
Overview
- Lead the design and implementation of scalable, high-performing data platforms for advanced analytics.
- Define enterprise data architecture strategies ensuring reliability and efficiency across data structures.
- Optimize data flows and pipelines to reduce time-to-insight for finance and leadership teams.
- Establish standards for data governance, lineage, and model reusability to elevate data quality.
- Collaborate with cross-functional teams to translate business requirements into scalable data solutions.
- Evaluate and implement new tools and architectures to enhance platform performance.
- Provide technical expertise in Databricks, Snowflake, and other modern data platforms.
- Support hybrid work arrangements, fostering collaboration and professional development.
Key Responsibilities & Duties
- Design enterprise-grade data architectures leveraging Databricks, Snowflake, or similar platforms.
- Develop efficient ELT/ETL workflows using Spark, Python, and SQL for data ingestion and transformation.
- Create and maintain dimensional, normalized, and semantic data models for analytics.
- Lead integration design of source systems ensuring alignment with data warehouse schemas.
- Enforce data governance policies, lineage tracking, and metadata standards.
- Optimize query performance and implement data caching strategies for efficiency.
- Collaborate with engineers, BI developers, and analysts to deliver scalable solutions.
- Evaluate tools and frameworks to enhance data platform scalability and performance.
Job Requirements
- Bachelor of Science (BS) degree in a relevant field.
- 8+ years of experience in data architecture, engineering, or BI roles.
- Expertise in Databricks, Snowflake, SQL, Python, and Spark.
- Proficiency in data modeling principles and designing lakehouse architectures.
- Experience with financial data structures and legal practice management systems.
- Familiarity with AWS, Azure, GCP, Power BI, and Tableau.
- Strong analytical, problem-solving, and technical communication skills.
- Preferred certifications: Databricks Certified Data Engineer, Snowflake SnowPro Advanced.
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