
Enterprise Data Architect
12 hours ago
About the Role:
As a key player in our organization's data-driven growth, we are seeking an accomplished Chief Data Strategist to lead the development of our enterprise-scale data ecosystem. The ideal candidate will possess exceptional technical expertise in data modeling, databases, cloud platforms, and integration frameworks, combined with strong leadership skills to mentor engineers and partner with stakeholders.
Key Responsibilities:
- Technical (70%): Design and implement scalable and secure data architecture, including data lakes, warehouses, and real-time streaming solutions.
- Develop, optimize, and maintain complex data pipelines (ETL/ELT) for structured and unstructured data across multiple systems.
- Create and maintain conceptual, logical, and physical data models to ensure consistency, reuse, and governance.
- Optimize database performance (SQL/NoSQL) and implement partitioning, indexing, and query tuning strategies.
- Deploy and manage data solutions using cloud-native tools (AWS Glue, Redshift, Azure Synapse, GCP BigQuery, etc.).
- Implement data security frameworks (encryption, access control, GDPR, HIPAA compliance, etc.).
- Introduce and oversee metadata management, MDM, and data lineage tracking using industry-standard tools.
- Stay current with emerging technologies (e.g., AI/ML data pipelines, graph databases, lakehouse platforms).
- Leadership & Strategic (30%): Serve as the data architecture authority, defining standards, frameworks, and best practices.
- Lead and mentor Data Engineers, BI Developers, and Analysts in architecture principles and implementation.
- Partner with Product, Engineering, and Business teams to translate requirements into data-driven solutions.
- Drive adoption of data governance and data quality frameworks across the organization.
- Provide technical leadership in solution design reviews, architecture boards, and strategic planning sessions.
- Evaluate vendor tools and make recommendations for long-term scalability and cost optimization.
Required Skills & Qualifications:
- Strong expertise in SQL, Python, or Scala for data processing and transformations.
- Proven experience with ETL/ELT frameworks (dbt, Informatica, Talend, Apache NiFi, Airflow).
- Hands-on experience with cloud data platforms (AWS: Redshift/Glue/Lake Formation; Azure: Synapse/Data Factory; GCP: BigQuery/Dataflow).
- Knowledge of real-time data streaming (Kafka, Kinesis, Spark Streaming).
- Strong foundation in data modeling (3NF, dimensional, star/snowflake schemas, data vault).
- Familiarity with DevOps for data (CI/CD pipelines, Infrastructure as Code, Terraform, Git).
- Knowledge of big data frameworks (Hadoop ecosystem, Spark).
- Understanding of data security, governance, and compliance frameworks.
- Strong communication skills with the ability to influence and guide technical and business teams.
Qualifications:
- Bachelor's/Master's degree in Computer Science, Data Engineering, or related field.
- 8+ years of experience in data engineering/architecture roles with at least 3+ years as a Data Architect.
- Proven expertise in designing and implementing enterprise-scale, cloud-based data ecosystems.
- Relevant certifications preferred (AWS Certified Data Analytics, Google Professional Data Engineer, Azure Data Engineer Associate).
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