Senior Data Engineer Moldova

 

YOUR PURPOSE:

• You combine solid data engineering, data modelling, data architecture, integration knowledge with your business understanding, and strong analytical skills that enable you to deliver the expected benefits to the business.
• Work with a team of Data engineers and Data Analysts to deliver the work based on the priority and make sure it’s delivered at the right timeline with industry leading best practices.  
• Implement critical programs by collaborating with various stakeholders and act as a Integration expert / Data solution architect to deliver end to end solution.
• You must have excellent communication skills to collaborate with the technical aspects of project delivery including presenting technical and business concepts to a variety of business stakeholders. When a business user faces significant issues, you step in to find the cause and suggest a solution. Next to that, you can influence and consult (providing options with pros, cons, and risks) around all key technical decisions during project delivery and process improvements.
• Leverage industry best practice to help define and implement a global data platform strategy which supports the centralisation, normalisation, and democratisation of the client's vast data stores. You’ll ‘dig in’ and become an expert on our EPC, global asset management, and Oil field operations datasets. 

RESPONSIBILITIES:

• Architecting and defining data flows for big data/data lake use cases 
• Excellent knowledge on implementing full life cycle of data management principles such as Data Governance, Architecture, Modelling, Storage, Security, Master data, and Quality.  
• Act as a coach and provide consultancy services and advice to data engineers by offering technical guidance, and ensuring architecture principles, design standards and operational requirements are met.  
• Participate in the Technical Design Authority forums.
• Collaborates with analytics and business stakeholders to improve data models that feed BI tools, increasing data accessibility, and fostering data-driven decision making across the organization.  
• Work with team of data engineers to deliver the tasks and achieving weekly and monthly goals, also to guide the team to follow the best practices and improve the deliverables.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
• Responsible for estimating the cluster size, core size, monitoring, and troubleshooting of the data bricks cluster and analysis server to produce optimal capacity for computing data ingestion.
• Deliver master data cleansing and improvement efforts; including automated and cost-effective solutions for processing, cleansing, and verifying the integrity of data used for analysis.
• Expertise in securing the big data environment including encryption, tunnelling, access control, secure isolation.
• To guide and build highly efficient OLAP cubes using data modelling techniques to cater all the required business cases and mitigate the limitation of Power BI in analysis service.
• Deploy and maintain highly efficient CI/CD devops pipelines across multiple environments such as dev, stg and production.
• Strictly follow scrum based agile approach of development to work based on allocated stories.

 

REQUIREMENTS:

 

• Comprehensive knowledge on data extraction, Transformation and loading data from various sources like Oracle, Hadoop HDFS, Flat files, JSON, Avro, Parquet and ORC. 
• Experience defining, implementing, and maintaining a global data platform 
• Experience building robust and impactful data visualisation solutions and gaining adoption
• Extensive work experience onboarding various data sources using real-time, batch load or scheduled loads. The sources can be in cloud, on premise, SQL DB, NO SQL DB or API-based
• Expertise in extracting the data through JSON, ODATA, REST API, WEBSERVICES, XML.
• Expertise in data ingestion platforms such as Apache Sqoop, Apache Flume, Amazon kinesis, Fluent, Logstash etc.
• Hands on experience in using Databricks, Pig, SCALA, HIVE, Azure Data Factory, Python, R
• Operational experience with Big Data Technologies and Engines including Presto, Spark, Hive and Hadoop Environments
• Experience in various databases including Azure SQL DB, Oracle, MySQL, Cosmos DB, MongoDB
• Experience supporting and working with cross-functional teams in a dynamic environment.