
Data Architect
4 days ago
Job Summary:
We are seeking an experienced and detail-oriented Data Architect to design and optimize our enterprise data systems. The ideal candidate will have at least 8 years of experience in data modeling, database architecture, and analytics infrastructure, with a strong background in SQL/NoSQL databases, data pipelines, cloud platforms, and data governance. This role is critical to shaping how data is stored, processed, and consumed across the organization.
Key Responsibilities:
• Design and implement data architecture strategies that support business objectives.
• Define data models, data flow diagrams, and schemas across structured and unstructured data.
• Lead the design of data pipelines and ETL/ELT workflows for ingestion, transformation, and storage.
• Architect and manage data lakes, data warehouses, and real-time data platforms.
• Ensure data quality, integrity, security, and compliance with regulatory requirements.
• Collaborate with engineering, product, and analytics teams to align data strategies with business goals.
• Optimize database performance, indexing strategies, and query tuning.
• Establish and enforce data governance standards and best practices.
• Evaluate and integrate new tools, platforms, and technologies to improve the data ecosystem.
• Document data architecture decisions, technical designs, and data dictionaries.
Soft Skills & Competencies:
• Strong analytical and problem-solving skills.
• Excellent verbal and written communication to bridge technical and business teams.
• Ability to lead data strategy discussions and influence architecture decisions.
• Experience with project and stakeholder management.
• Strategic mindset with attention to long-term scalability and maintainability.
Technical Skills & Experience:
•
5+ years of experience in data engineering or architecture roles.
• Expertise in relational databases (e.g., MySQL, PostgreSQL, Oracle) and NoSQL databases (e.g., MongoDB, Cassandra).
• Strong experience with data modeling tools (e.g., ERwin, dbt, Lucidchart).
• Hands-on with big data technologies such as Hadoop, Spark, Hive, Presto.
• Proficiency in ETL/ELT tools (e.g., Apache NiFi, Talend, Informatica, Airflow).
• Experience with cloud-based data platforms (e.g., AWS Redshift, GCP BigQuery, Azure Synapse).
• Strong knowledge of data warehousing concepts, data lakes, and real-time streaming architectures.
• Familiarity with Kafka, Kinesis, or other event streaming tools.
• Proficient in Python, SQL, and optionally Java or Scala for data processing.
• Solid understanding of data security, encryption, access control, and compliance standards (GDPR, HIPAA, etc.).
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