
Enterprise Cloud Data Architect
1 week ago
Job Summary:
The ideal candidate for this position will have a strong understanding of data modeling, databases, and cloud platforms. They will be responsible for owning the end-to-end data architecture strategy and actively engaging in the design, development, and optimization of our data ecosystem.
Key Responsibilities- Technical Expertise
- Design and build scalable and secure enterprise data architectures, including data lakes, warehouses, and real-time streaming solutions.
- Develop, optimize, and maintain 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
- Define standards, frameworks, and best practices for data architecture.
- 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.
Requirements
- 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).
What We Offer
We offer a competitive compensation package, opportunities for professional growth and development, and a collaborative work environment.
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