DESCRIPTION:
Ensure data quality, consistency, and security across all data platforms.
Collaborate with data scientists and analysts to understand data requirements and provide efficient data access methods.
Integrate various data sources and APIs into our data ecosystem.
Implement and optimize data storage solutions, including data warehouses and data lakes.
Automate data workflows and implement monitoring and alerting systems.
Design, develop, and maintain scalable data pipelines and ETL processes.
Stay up- to- date with emerging technologies and recommend improvements to our data architecture.
Implement data governance policies and procedures.
Optimize query performance and data retrieval processes.
Develop and maintain data models, schemas, and data dictionaries.
REQUIREMENTS:
Must have
Experience with data modeling, data warehousing concepts, and dimensional modeling.
Proficiency in big data technologies (e.g., Hadoop, Spark, Hive).
Bachelor&039;s or Master&039;s degree in Computer Science, Engineering, or a related field.
5+ years of experience in data engineering or similar roles.
Certifications in relevant data platforms or cloud technologies (AWS, GG, Azure, Databrick, Dataiku, Snowflake)
Experience with ELT/ETL open source frameworks (DBT, Fivetran)
Experienced in working with large ERP systems and has participated in building ETL pipelines from the analysis and design phases.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
Extensive experience with SQL, NoSQL, Vector databases
Flexible, with strong problem- solving skills and attention to detail
Familiarity with data visualization tools (e.g., Tableau, Power BI).
Experience with version control systems (e.g., Git) and CI/CD pipelines.
Strong programming skills in Python, Scala, or Java.
Nice to have
Experience with streaming data processing (e.g., Kafka, Flink).
Agile mindset
Certifications in relevant data platforms or cloud technologies (AWS, GG, Azure, Databrick, Dataiku)
Knowledge of machine learning pipelines and MLOps practices.
Experience with database migration projects
Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
Familiarity with other data analytics tools such as Power BI, Tableau, etc.
Experience with data governance and compliance requirements (e.g., GDPR, CCPA).
