VAYUZ Technologies | Data Engineer
14 hours ago
Data Collection and Integration
Collect data from various sources, including databases, APIs, external data providers, NoSQL, unstructured data and streaming sources. Design and implement efficient data pipelines to ensure a smooth flow of information into the data warehouse or storage system.
Data Storage and Management
Choose appropriate database systems, optimize data schemas, and ensure data quality and integrity. Consider scalability and performance to handle large volumes of data.
ETL (Extract, Transform, Load) Processes
Design ETL pipelines to transform raw data into a format suitable for analysis. This involves data cleansing, aggregation, and enrichment, ensuring the data is usable.
Big Data Technologies and Cloud Computing
Big data and OLAP technologies such as Google Cloud Big Query, Hadoop and Spark to efficiently process and analyze massive datasets.
Enterprise Data Governance
Define and ensure adherence to the Enterprise Data Governance framework for data practices, policies, and standards both at a technical and a functional level. Work closely with various data owners to develop and implement Data Governance Framework.
Distributed Systems
Handle huge data volumes and ensure fault tolerance. Understanding how distributed systems work is essential for data engineers.
Streaming Data (CDC)
Work with streaming technologies like Qlik Replicate, Informatica CDC, Apache Kafka to handle and analyze data as it flows in.
Qualification and experience:
15+ years of hands-on experience in the field of Data Integration and Governance; out of which at least 10 years of leading a team of Data Engineers and Data Governance specialists.
Previously held roles leading Data Engineering teams for dynamic, growing organizations.
Natural enthusiasm to keep up to date on emerging technologies and methodologies to continually improve and advance data solutions where possible.
Knowledge and experience in building end-to-end Data Pipelines.
Knowledge and experience in building Enterprise Data Governance Lifecycle based on the Maturity Model.
Experience in implementing Data Availability, Data Quality, Data Catalogue, Data Lineage & Data Security initiatives across the Enterprise. Having worked in a regulated industry would be a plus.
Experience in defining and enforcement of Data Engineering and Governance principles and policies across the Enterprise.
Knowledge of Relational and NoSQL databases. Hands-on experience in T-SQL / PL-SQL programming.
Bachelor's degree in IT, Computer Science, or a related field; Master's degree will be a plus.
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