Data Architect
2 weeks ago
At Minutes to Seconds, we're seeking a skilled Data Architect to join our team. As a Data Architect, you will be responsible for designing, implementing, and managing the data architecture for the company. You will work closely with cross-functional teams to define data requirements, oversee data integration processes, and ensure data quality and governance standards are maintained.
Key Responsibilities- Data Architecture Design: Develop and implement a scalable data architecture to support various business needs, including data warehousing, data lakes, and analytics.
- Data Modeling: Design logical and physical data models that adhere to best practices and align with business objectives.
- Data Integration: Oversee data integration strategies, ETL/ELT processes, and data pipelines to support data migration, transformation, and loading between systems.
- Data Governance: Establish and enforce data governance policies, ensuring data accuracy, accessibility, and security across all systems.
- Technology Evaluation: Assess, recommend, and implement data management tools, database technologies, and cloud solutions that best meet organizational needs.
- Collaboration: Work closely with data engineers, data scientists, business analysts, and other stakeholders to define data requirements and ensure cohesive data strategies.
- Performance Optimization: Identify and address data architecture inefficiencies to improve system performance and data retrieval times.
- Documentation: Maintain comprehensive documentation for data structures, data flows, and integration processes to support ongoing maintenance and team understanding.
- Education: Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field.
- Experience: 5+ years of experience in data architecture, data modeling, or data management roles.
- Technical Skills: Proficiency in database management systems, such as SQL Server, Oracle, MySQL, and NoSQL databases like MongoDB or Cassandra. Expertise with cloud platforms (AWS, Azure, Google Cloud) and data services (Redshift, Snowflake, BigQuery). Strong understanding of data modeling tools (e.g., ER/Studio, Erwin) and data integration tools (e.g., Informatica, Talend). Knowledge of ETL/ELT processes and tools, data warehousing, and data lake architecture. Familiarity with data governance and data quality frameworks.
- Analytical Skills: Strong problem-solving skills and the ability to analyze complex data structures and flows.
- Communication Skills: Excellent written and verbal communication skills with the ability to translate complex data requirements into business-friendly language.
- Experience with machine learning and AI data pipelines.
- Knowledge of data visualization tools like Power BI, Tableau, or Looker.
- Familiarity with big data technologies like Hadoop, Spark, and Kafka.
- Certification in data architecture or cloud platforms (e.g., AWS Certified Data Analytics, Azure Data Engineer).
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