Data Engineer

The Data Engineer will be working on building and maintaining complex data pipelines, Assemble large and complex datasets to generate business insights and to enable data driven decision making and support the rapidly growing and dynamic business demand for data.

As a Data Engineer you will have an opportunity to collaborate and work with various teams of Data Scientists, Database Developers and Managers, Software Dev Engineers, and Program managers to determine how best to design, implement and support solutions.

• Design, implement and support analytical data platform solutions for data driven decisions and insights.
• Design data schema and operate internal data warehouses & SQL/NOSQL database systems.
• Work on different data model designs, architecture, implementation, discussions and optimizations.
• Interface with other teams to extract, transform, and load data from a wide variety of data sources, big data technologies like EMR, RedShift, Elastic Search etc.
• Work on SQL technologies on Hadoop such as Spark, Hive, Impala etc.
• Help continually improve ongoing analysis processes, optimizing or simplifying self-service support for customers
• Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.
• Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
• Enjoy working closely with your peers in a group of talented engineers and gain knowledge.
• Be enthusiastic about building deep domain knowledge on various GSII AFP domains.
• Own the development and maintenance of metrics, reports, analyses, dashboards, etc. to drive key business decisions.

Requirements

• Candidates must have a degree in Computer Science or Engineering or related field, and 3+ years of industry experience as a Data Engineer or in a similar role.
• Hands on experience in languages like Python, Java, Scala, etc.
• Working knowledge of RDBMS, Big Data, SQL, NOSQL, ETL and Data-warehousing.
• Experience working with distributed systems and big data processing technologies (Hadoop, Hive, Hbase, Spark, EMR, etc.).
• Candidate must have good written and oral communication skills, be a fast learner and have the ability to adapt quickly to a fast-paced development environment.
• Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations.
• Knowledge of cloud services such as AWS or equivalent.
• Knowledge on different reporting/visualization tools in the industry.
• Sharp problem-solving skills and ability to resolve ambiguous requirements .

Benefits

• Control Risks offers a competitively positioned compensation and benefits package that is transparent and summarised in the full job offer.
• We operate a discretionary bonus scheme that incentivizes, and rewards individuals based on company and individual performance
• Control Risks supports hybrid working arrangements, wherever possible, that emphasize the value of in-person time together - in the office and with our clients - while continuing to support flexible and remote working.