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

8–10 years of experience in data roles, with 3–5 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.

DATA ARCHITECT - Morning shift