
Chief Data Engineer
3 days ago
We are seeking an accomplished data professional to drive our organization's data architecture strategy and spearhead the design, development, and optimization of our data ecosystem.
This role demands technical expertise in data modeling, databases, cloud platforms, and integration frameworks, combined with leadership skills to mentor engineers and partner with stakeholders to ensure our data foundation supports business growth and innovation.
Key Responsibilities:
- 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:
- 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.
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.
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