
Enterprise Cloud Data Architect
4 days ago
We are seeking a highly skilled Data Architect to lead the development and implementation of our data ecosystem.
This is a hands-on role that requires technical expertise in data modeling, databases, cloud platforms, and integration frameworks.
Key Responsibilities- Technical (70%)
- Design and implement scalable enterprise data architecture, 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).
- Implement data security frameworks (encryption, access control, GDPR compliance).
- 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).
- Serve as the Data Architecture Authority
- 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.
- Strong Expertise in SQL, Python, or Scala
- 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
- 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.
- Excellent Communication Skills
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.
- Relevant certifications preferred (AWS Certified Data Analytics, Google Professional Data Engineer, Azure Data Engineer Associate).
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