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Description:
Analytical Engineer with strong Data Analyst and Data Modelling expertise required to translate business requirements into structured, analytics-ready datasets. Must have experience in Data Vault 2.0 / dimensional modelling and advanced SQL for data transformation and analysis. Role focuses on data profiling, validation, and delivery of trusted data for reporting and analytics. Experience with Azure/Databricks and enterprise data environments preferred. Strong stakeholder engagement and ability to bridge business and technical data requirements essential.
Must Have Skills
- Data Analysis
- Data Governance
- Data Modeling tool
Nice to Have Skills
- Business writing skills
- Governance, Risk and Controls
- Principles of project management
- Relevant regulatory knowledge
- Relevant software and systems knowledge
ROLES AND RESPONSIBILITIES:
You will be responsible for architecting, implementing, and optimizing Dremio-based data Lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.
- Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
- Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
- Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
- Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
- Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
- Support self-service analytics by enabling governed data products and semantic layers.
- Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
- Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.
IDEAL CANDIDATE:
- Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
- 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
- Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
- Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
- Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
- Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
- Excellent problem-solving, documentation, and stakeholder communication skills.
PREFERRED:
- Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
- Exposure to Snowflake, Databricks, or BigQuery environments.
- Experience in high-tech, manufacturing, or enterprise data modernization programs.


