Data Engineer at Tetra Pak

Job Description

• We are looking for a Data Engineer who will be a key player in our Product Development Outsourcing business. Our engineers love to learn and have a passion for technology.
• They’re known for their expertise in solving the most complex tech challenges while having fun and being part of a dynamic and collaborative team.
• In this role, you’ll join a team creating the financial services and banking industry of tomorrow, helping an innovative fintech company that is committed to transforming the retail space in Africa. Based at our clients’ location on Victoria Island, you’ll build next generation engines and services.

A career in tech. Work with the biggest and best names in technology:

• For more than a decade, we’ve been growing, learning, and helping talented people like you advance their technology careers. At Tek Experts, you’ll build your expertise while your achievements are elevated and celebrated.
• We’ll be with you from the start with the training and tools to ensure you succeed. Plus, you’ll get ongoing learning and development opportunities, and thrive as part of our supportive work culture.
• Being a part of Tek Experts means you can develop your career across multiple clients and technologies and be at the leading edge of development now, and in the future.
• We know diverse teams make the strongest teams. Our team members come from all cultures, perspectives, and experiences. Sound like you? Keep reading to see the details of the role and take the next step in your career by applying today.

Leverage your engineering skills in the financial services industry:

• We’re seeking a diligent Engineer to connect and model complex distributed data sets to build repositories like data warehouses and data lakes. 
• You’ll leverage your expertise in machine learning, data mining, and information retrieval to design, prototype, and build next-generation engines and services.
• This will be a challenging but rewarding role that requires effective communication and collaboration as well as a keen attention to detail and the ability to learn and adapt to emerging technologies.

Responsibilities

• Define the data lifecycle, including data models and data sources for analytics platforms
• Create and maintain an optimal data pipeline and architecture
• Build analytics tools and conduct advanced statistical analysis to provide actionable insights, identify trends, and measure performance
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, and more
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies
• Perform aggregations on data across various warehousing models
• Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs
• Keep data secure and work closely with database teams on topics related to data requirements, cleanliness, accuracy, and others

Qualifications

• Bachelor's or equivalent Degree in Computer Science or another related field
• 3-5 years of direct experience in a statistical and/or data science role
• Experience working with large data sets, simulation/ optimization, and distributed computing tools
• Hands-on knowledge of data extraction and transformation tools - traditional ETL tools (Informatica, Alteryx) as well as the latest big data tools
• Experience working with large datasets, relational databases (SQL), and distributed systems (Hadoop, Hive)
• Extensive experience with R and/or SAS. Knowledge of other statistical software like SPSS, RapidMiner, and others is a plus
• Knowledge of data architecture and experience defining data retention policies, monitoring performance, and advising any necessary infrastructure changes
• Comfortability with developing dashboards (Tableau, Power Bi, Qlik, etc.) and data analytics models (R, Python, Spark)
• Strong analytical, communication, and problem-solving skills
• Professional fluency in English is vital, both written and spoken