Roles & Responsibilities
Data Architecture & System Design
- Design scalable, high-performance data pipelines for batch and real-time processing.
- Implement Lambda and Kappa architectures, event-driven and microservices data patterns.
- Apply data mesh principles and ensure robust metadata management and data lineage.
- Lead Master Data Management (MDM) initiatives and maintain enterprise-wide data standards.
Data Modeling & Database Design
- Develop and maintain data warehouse models using Star Schema, Snowflake Schema, Dimensional modeling (Kimball), Data Vault 2.0, and SCD Types 1-6.
- Optimize database design with strategic normalization/denormalization, partitioning, sharding, and indexing.
- Implement advanced query optimization and performance tuning strategies.
Cloud Platforms & Data Tools
- Work with AWS (Redshift, S3, Glue, Lake Formation, Athena) or Azure (Synapse, Data Factory, Databricks, ADLS).
- Manage data warehouses and lakes: Snowflake, Redshift, BigQuery, Databricks, Azure Synapse.
- Implement ETL/ELT pipelines using dbt, Apache Airflow, Informatica, Talend, SSIS, Fivetran, or Stitch.
- Manage streaming data via Kafka, Kinesis, Event Hubs, Spark Streaming, or Flink.
Data Governance & Security
- Define and enforce data governance policies, quality frameworks, and stewardship models.
- Maintain compliance with GDPR, HIPAA, LGPD, and SOC2.
- Implement data security best practices including encryption, row/column-level security, IAM, masking, tokenization, and audit logging.
Performance & Optimization
- Conduct query optimization, capacity planning, cloud cost optimization, and performance benchmarking.
- Monitor pipelines and systems using tools such as DataDog, CloudWatch, or Grafana.
Leadership & Stakeholder Management
- Provide technical leadership: code reviews, establishing standards, technical decision-making.
- Communicate effectively with C-level executives and business stakeholders to translate requirements into technical solutions.
- Facilitate design workshops, manage roadmaps, and drive strategic technical initiatives.
Programming & DevOps Skills
- Advanced SQL (CTEs, window functions, query optimization), Python or Scala, and scripting (Bash/PowerShell).
- Experience with CI/CD, Git, Terraform, CloudFormation, ARM templates, Docker, and Kubernetes (basic).
Complementary Knowledge
- Knowledge of BI tools (Tableau, Power BI, Looker), semantic layers, data marts, and business KPIs.
- Familiarity with ML pipelines, feature stores, and MLOps is desirable.
Current Trends
- Modern Data Stack (dbt, Snowflake), real-time analytics, cloud-native architectures, data mesh, and DataOps practices.
Qualifications
- 810 years of experience in data roles, with 35 years in architecture or designing complex data systems.
- Strong technical expertise across data warehousing, cloud platforms, ETL/ELT, streaming, and databases.
- Demonstrated experience in data governance, security, and performance optimization.
- Proven leadership, stakeholder management, and strategic planning skills.
