Data Engineer
Data Engineer
Posted on :
22-05-2025
Employer Active
1 Vacancy
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Monthly Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
22-05-2025
Job Description
Remote Contract position
Minimum Requirements:
- BSc Engineering/ Computer Science/ relevant IT qualification
- 4 years experience in a Data domain role (Data engineering) / Data modelling experience in relevant environment
- Data warehouse technical experience definition /implementation/ integration.
- Strong programming skills in Python and DBA skills (SQL/PSQL/DynamoDB or other).
- Experience with data pipeline and ETL tools and reporting/analytics tools including but not limited to any of the following combinations (1) SSIS and SSRS (2) ETL Frameworks (3) Data conformance (4) Caching (5) Spark (6) AWS data builds.
- Experience with data modelling data governance and data quality.
- Strong problemsolving skills and ability to work in a fastpaced environment.
- Strong communication skills and ability to work in a team.
- Expertise in Machine Learning (ML) and deep learning frameworks.
- Explaining the thinking behind simple ML algorithms.
- Proficiency in all aspects of model architecture data pipeline interaction and metrics interpretation.
Ideal:
- Experience with Big Data technologies such as Hadoop and Spark.
- Experience with containerization technologies such as Docker and Kubernetes.
Responsibilities:
- Develop and implement portfolio Data modelling assurance and utilisation strategies and frameworks that align with enterprise approved governance data and technology strategy and the Data COE.
- Lead the implementation of these strategies within the portfolio.
- Responsible for reporting activities at a portfolio level that provides insights into the portfolio data assurance landscape strategy and roadmap and key metrics and indicators.
- Serve as though leader and guide in the data domain by sharing knowledge identifying problems patterns trends and support the development of relevant BI and MI solutions.
- Design and implement scalable and robust processes for ingesting and transforming complex datasets.
- Contribute to the development of architectural frameworks apply architecture principles and drive the development of data architecture models within the organisation.
- Design and develop data models using dimensional modelling and data vault techniques and ensure stated business requirements are met by these models.
- Focused on data stewardship and curation the data engineer enables the data scientist to run their models and analyses to achieve the desired business outcomes.
- Architect train validate and test advanced analytics / machine learning models using enterprisegrade software engineering practices.
- Collaborate with data scientists and analysts to understand data requirements and ensure that data models and prompt engines function as expected and data is accessible and usable.
- Design develops and maintain automated scalable data pipelines that improve estate performance stability and auditability.
- These include data pipelines for ETL processing.
- Monitor and troubleshoot data pipeline issues.
- Define implement and integrate with enterprise data lake and data warehouse solutions (cloud and onpremises).
- Ingest large complex data sets that meet functional and nonfunctional requirements.
- Enable the business to solve the problem of working with large volumes of data in diverse formats and in doing so enable innovative solutions.
- Engineer data in the appropriate formats for downstream customers risk and product analytics or enterprise applications.
- Proficiency in managing test data ensuring data integrity and maintaining data privacy and security standards.
- Provide technical leadership and mentorship to junior intermediate and senior data specialists.
- Leadership and Team Management
- Strong leadership skills to guide and mentor squads setting clear goals and expectations for team members.
- Competence in managing and coordinating efforts including resource allocation workload distribution and task prioritisation.
- Ability to foster a collaborative and innovative team culture that promotes excellence in data engineering practices.
- Stakeholder Communication
- Manage stakeholder communication providing regular updates on data activities milestones and risks.
- Excellent communication and presentation skills for effectively conveying data status datadriven insights and recommendations to stakeholders at all levels.
- Ability to collaborate with crossfunctional teams and provide visibility into data/modellingrelated matters.
- Ethical and Compliance Awareness
- Understanding of ethical considerations in data engineering including data privacy security and confidentiality.
- Awareness of industryspecific compliance standards regulations and best practices and the ability to ensure adherence in data engineering processes.
- Skill in conducting ethical and compliant testing and data assurance activities.
- Continuous Learning and Adaptability
- Commitment to staying updated with emerging data engineering trends technologies and industry developments.
- Willingness to pursue certifications training and continuous learning opportunities to enhance and adapt data engineering skills.
- Ability to quickly adapt to evolving project requirements and data paradigms.
Employment Type
Full Time
Key Skills
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