
Senior Data Platform Engineer
3 weeks ago
About the Company
Petroleum Development Oman is the leading exploration and production company in the Sultanate of Oman. The Company delivers the majority of the country's crude oil production and natural gas supply.
Purpose of the JobThe role of a Senior Data Platform Engineer is to design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals. Responsible for improving and scaling the data lake and solving complex data problems to ensure the creation of a scalable, performance, accessible single source of truth. Additionally, advises, consults, mentors, and coaches others in the field.
Education & Experience- Bachelor's degree in computer science or information management or related field.
- Minimum of 10 years' experience in data and analytics management.
- 8+ years of experience in data engineering and data platform management, preferably with digitally-native or digitally advanced organizations.
- Must have experience in the product and platform operating models.
- Must have experience in Digital Product and Platform.
- Hands-on experience in building, scaling and maintaining a data lake for a major corporation.
- Expertise in SQL and at least one programming language (Python, Scala, Java, R, etc.).
- Experience developing and maintaining big data solutions for structured and un-structured data including real-time streaming (e.g., with Kafka).
- Experience with developing data solutions on cloud computing services and infrastructure.
- Database development knowledge using e.g., Hadoop or BigQuery and knowledge of a variety of relational, NoSQL, cloud database technologies (e.g. Databricks or Snowflake) and demonstrate strong proficiency in modern data management tools.
- Experience in using data cataloging tools that leverage metadata management to create an inventory of data assets within an organization. Experience in Master Data Management technologies. Familiar with BI tools such as Tableau, Power BI, Looker, Shiny.
- Exposure to integrating multi-Lakes or multiple Data Platforms environments using data virtualization tools (e.g. Microsoft Fabric, Denodo, etc.).
- Strong conceptual knowledge of data and analytics, such as database design, dimensional modeling, ETL, reporting tools, data governance, data warehousing, structured and unstructured data.
- Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics.
- Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals.
- Advise, consult, mentor, and coach other data and analytic professionals on data standards and practices.
- Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.
- Lead the evaluation, implementation, and deployment of emerging tools and processes for analytic data engineering in order to improve data engineering and science productivity.
- Partner with enterprise and solutions architects to develop technical architectures for the full integration of the central data platform in other applications and the infrastructure.
- Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics to ensure availability of future capability requirements on the data platform.
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