JobWebKenya

Job Purpose : Reporting directly to the Chief Data Officer (CDO), this role will involve working with the CDO to support the collection and channeling of massive amounts of data for use by the various teams to drive business insights.. Deploy and maintain data science, machine learning and other data products using best practices in engineering.. Proven working experience (6+ years) as a Data Engineer, Software Engineer or related preferably in the financial services industry.. Strong programming experience in two major data programming languages – Python and Scala (preferred), Go or Java.. Strong experience with big data technologies such as Spark, Kafka, Kinesis, Airflow, Hadoop, Hive, Databricks, Snowflake etc.

data engineering

Job Description
With over one hundred and thirty branches in Kenya, Tanzania, Uganda, and Burundi, some of which are 24/7 digital branches, DTB is committed to enabling people to advance with confidence and success. The Bank’s heritage and values are articulated in its brand promise, Achieve More, and brought to life through an engaged diverse workforce. Job Purpose : Reporting directly to the Chief Data Officer (CDO), this role will involve working with the CDO to support the collection and channeling of massive amounts of data for use by the various teams to drive business insights. Key Responsibilities: Identify gaps in data architecture and implement data pipelines that collect, manage, and convert raw data for data analysts, data scientists, and business intelligence analysts to analyze and interpret. Design, develop, and maintain data pipelines for use in various analysis within the Bank. Provide technical leadership and mentoring to the other members of the team. Build, test, and maintain data pipeline architectures in line with business requirements. Integrate large, complex data sets that meet business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability. Deploy and maintain data science, machine learning and other data products using best practices in engineering. Requirements:
Academic: A bachelor’s degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science or equivalent. Master’s degree in an IT/Quantitative or related field is an added advantage. Certifications in Cloud (Azure, AWS) is an added advantage. Professional: Proven working experience (6+ years) as a Data Engineer, Software Engineer or related preferably in the financial services industry. Experience building and optimizing big data pipelines, architectures, and data sets. Strong programming experience in two major data programming languages – Python and Scala (preferred), Go or Java. Strong experience with big data technologies such as Spark, Kafka, Kinesis, Airflow, Hadoop, Hive, Databricks, Snowflake etc. Expertise in SQL and NoSQL databases, models, and frameworks. Working experience in software development, microservices, and DevOps. A strong understanding of the software development lifecycle, with proficiency in version control with Git, CI/CD, and containerization (Docker). Demonstrated leadership skills with a good command of the English language (oral and written). Strong planning, effective communication and presentation skills, ability to listen and influence. Personal Competencies: Team player who can collaborate with different business units. Knowledge of DevOps and Cloud engineering. Experience in software development using object-oriented languages. Good understanding of data and software architecture. Continuous learning mindset. #J-18808-Ljbffr

START NEW SEARCH