Data Engineer

s a Data Engineer you will design, build and operate scalable data solutions across on-premises and cloud (AWS) platforms, with a strong emphasis on high-performance data processing, data modelling, Oracle database optimisation and the delivery of robust ETL/ELT pipelines. You will work closely with data analytics, BI, data science, and business stakeholders to ensure data availability, integrity, and performance. Working Hours: Mon-Fri Working Location: Central Salary Package: Up to $7,000 (basic) + AWS + VB Key Responsibilities: Architect, build and maintain end-to-end data pipelines (ingest, transform, load) to feed analytics, reporting and model development. Design and optimise data warehouses / data marts / data lakes supporting business intelligence, analytics and operational reporting. Lead database performance tuning efforts, particularly on Oracle (e.g., query optimisation, indexing, partitioning, statistics, execution plan analysis) to ensure high-availability and optimal throughput. Manage cloud-based data services on AWS (e.g., Redshift, RDS, Athena, S3, Glue) and integrate them with on-premises systems as needed. Collaborate with stakeholders (data scientists, analysts, business users, product teams) to translate business requirements into robust data solutions. Implement data quality, data governance and metadata management frameworks to ensure reliability and trust in the data. Monitor, troubleshoot and optimise data flows, storage, and compute resources for cost, performance and scalability. Mentor and guide more junior data engineers, review code, enforce best practices, and contribute to the continuous improvement of the data engineering function. Required Skills & Experience: Bachelor's or Master's degree in Computer Science, Information Systems, Engineering or a related discipline. 5+ years' experience in data engineering or related roles, working with large scale data systems. Strong expertise in Oracle database administration and optimisation: SQL performance tuning, indexing strategy, partitioning, execution plans, capacity planning. Proven experience working with AWS services for data (e.g., AWS RDS/Oracle, Redshift, S3, Glue, Athena, etc.). Solid programming skills in SQL and at least one other language (e.g., Python, Java). Experience designing and implementing ETL/ELT workflows, and data modelling for both OLAP and OLTP. Good understanding of data warehousing concepts: star/snow‐flake schemas, slowly evolving dimensions, fact/dimension modelling. Experience with cloud and hybrid architectures, data lakes, metadata management and data governance. Strong analytical, problem-solving and troubleshooting skills, especially under performance constraints. Excellent stakeholder management, communication skills, and ability to work cross‐functionally in a collaborative environment. Prior experience mentoring or guiding junior staff desirable. Nice to Have: Certification in AWS (e.g., AWS Certified Data Analytics or AWS Certified Database – Specialty). Experience with big-data technologies (e.g., Spark, Kafka, Hadoop) or real‐time streaming architectures. Exposure to cost‐optimisation of cloud data services. Familiarity with on‐premises to cloud migration projects (Oracle to AWS). What We Offer: Competitive salary and bonus structure. Flexible/hybrid work arrangements. Opportunity to work on strategic, high-impact data platforms across the organisation. Professional development support, certifications, conferences etc. A collaborative team environment with a culture of continuous improvement. By submitting your resume, you consent to the collection, use, and disclosure of your personal information per ScienTec's Privacy Policy (scientecconsulting.com/privacy-policy). This authorizes us to: Contact you about potential opportunities. Delete personal data as it is not required at this application stage. All applications will be processed with strict confidence. Only shortlisted candidates will be contacted. #J-18808-Ljbffr