Data Engineer (Decisioning)

Key Skills

Java Programming, Design of Experiment, Python Programming, SQL, Data science techniques, R Programming, Linux Operating system, Talend, ETL frameworks

Job Description

Afiniti uses data science and operations research to enhance human interactions in large enterprises by efficiently pairing customers or tasks with company representatives. Our primary focus is improving contact center interactions for sales, service, retention, collections, and customer satisfaction in fields ranging from telecommunications to healthcare to banking to hospitality. To ensure we’re delivering value, we measure performance using a real-time control group – routing a portion of calls using the client’s existing system and the majority of calls using our data-scientist-designed pairing and next best action recommendation strategies. Clients are billed on our incremental improvement, so model quality is central to our product.

Key responsibilities:

As a member of Data Engineering team, you will be working closely with AI and technical teams to analyze many non-standard and unique business problems and use creative problem solving to deliver actionable output. The role consists of wrangling and analyzing data with cutting edge tools, e.g. SQL, Talend (ETL) and Python. The data Engineer is expected to work collaboratively with the client, data scientists, researchers and software engineers. S/he is also expected to have very good problem-solving skills and think critically.

Requirements:

• BSc in Computer Science, Software Engineering, or any other relevant field
• Have 2-5 years of working experiences in relevant field and at least 1 Year of relevant Experience in Afiniti in case of an internal hiring.
• Implement ETL procedures and standards using SQL/Talend/Python for existing and new deployments.
• Automate, standardize and optimize all processes to reduce manual intervention.
• Design data models and implement effective data warehouse strategies i.e Slowly changing dimensions and concepts.
• Monitor all production ETL processes, perform root cause analysis on all incidents and resolve all production issues.
• Take responsibility for all the workflows and escalations.
• Analyze and interpret complex data and provide resolutions to all data issues.
• Support all Ad-hoc data development efforts and requests by developers and business users.
• Proactively work on identifying issues in the data and providing insights to AI team.
• Participate in at least one R&D project development.
• Good with finding hidden patterns in the data.
• Excellent Communication skills.

Plus

• Experience working in both Linux and Windows environment.
• Excellent in either Python or R