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Enterprise Data Architect
3 weeks ago
Job Summary:
We are seeking a highly skilled Data Architect to join our organization. The ideal candidate will have deep technical expertise in data modeling, databases, cloud platforms, and integration frameworks.
Main Responsibilities:
- Data Strategy & Design: Develop an end-to-end data architecture strategy that meets the needs of the business. This includes designing scalable and secure enterprise data architecture, including data lakes, warehouses, and real-time streaming solutions.
- Data Pipelines: Develop, optimize, and maintain data pipelines (ETL/ELT) for structured and unstructured data across multiple systems.
- Data Modeling: Create and maintain conceptual, logical, and physical data models to ensure consistency, reuse, and governance.
- Database Performance: Optimize database performance (SQL/NoSQL) and implement partitioning, indexing, and query tuning strategies.
- Cloud Deployment: Deploy and manage data solutions using cloud-native tools (AWS Glue, Redshift, Azure Synapse, GCP BigQuery, etc.).
- Data Security: Implement data security frameworks (encryption, access control, GDPR, HIPAA compliance, etc.).
- Metadata Management: Introduce and oversee metadata management, MDM, and data lineage tracking using industry-standard tools.
- Tech Leadership: Stay current with emerging technologies (e.g., AI/ML data pipelines, graph databases, lakehouse platforms).
Leadership & Strategic:
- Architecture Authority: Serve as the data architecture authority, defining standards, frameworks, and best practices.
- Team Leadership: Lead and mentor Data Engineers, BI Developers, and Analysts in architecture principles and implementation.
- Business Partnership: Partner with Product, Engineering, and Business teams to translate requirements into data-driven solutions.
- Data Governance: Drive adoption of data governance and data quality frameworks across the organization.
- Solution Design: Provide technical leadership in solution design reviews, architecture boards, and strategic planning sessions.
- Vendor Evaluation: Evaluate vendor tools and make recommendations for long-term scalability and cost optimization.
Key Skills & Qualifications:
- Programming Languages: Strong expertise in SQL, Python, or Scala for data processing and transformations.
- ETL/ELT Frameworks: Proven experience with ETL/ELT frameworks (dbt, Informatica, Talend, Apache NiFi, Airflow).
- Cloud Platforms: Hands-on experience with cloud data platforms (AWS: Redshift/Glue/Lake Formation; Azure: Synapse/Data Factory; GCP: BigQuery/Dataflow).
- Real-Time Streaming: Knowledge of real-time data streaming (Kafka, Kinesis, Spark Streaming).
- Data Modeling: Strong foundation in data modeling (3NF, dimensional, star/snowflake schemas, data vault).
- DevOps: Familiarity with DevOps for data (CI/CD pipelines, Infrastructure as Code, Terraform, Git).
- Big Data Frameworks: Knowledge of big data frameworks (Hadoop ecosystem, Spark).
- Data Security: Understanding of data security, governance, and compliance frameworks.
- Communication: Strong communication skills with the ability to influence and guide technical and business teams.
Qualifications:
- Degree: Bachelor's/Master's degree in Computer Science, Data Engineering, or related field.
- Experience: 8+ years of experience in data engineering/architecture roles with at least 3+ years as a Data Architect.
- Certifications: Relevant certifications preferred (AWS Certified Data Analytics, Google Professional Data Engineer, Azure Data Engineer Associate).