Job Description

The Data Engineer will be responsible for expanding and optimizing the data and

data pipeline architecture, as well as optimizing data flow and collection for cross

functional teams. The Data Engineer is an experienced data pipeline builder and

data wrangler who enjoys optimizing data systems and building them from the

ground up. The Data Engineer will support software developers, database

architects, data analysts and data scientists on data initiatives and will ensure

optimal data delivery architecture is consistent throughout ongoing projects. They

must be self-directed and comfortable supporting the data needs of multiple teams,

systems and products. The Data Engineer will be required to optimise or even re-

design the data architecture to support the next generation of products and data

initiatives. The Data Engineer is also responsible for the maintenance,

improvement, cleaning, and manipulation of data in the business’s operational and

analytics databases in order to understand and aid in the implementation of

database requirements, analyse performance, and troubleshoot any existent

issues.

The Data Engineer has to be an expert in SQL development further providing

support to the Data and Analytics in database design, data flow and analysis

activities. The position of the Data Engineer also plays a key role in the

development and deployment of innovative big data platforms for advanced

analytics and data processing.

• Key responsibilities for the Data Engineer include (but are not limited to):

• Create and maintain optimal data pipeline architecture, assemble large, complex data sets that meet functional and non-functional business requirements.

• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and ‘big data’ technologies.

• Implement analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

• 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 our data separated and secure across national boundaries through multiple data centres.

• Implement data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

• Work with data and analytics experts to strive for greater functionality in our data systems.

• Supports junior data engineering personnel by creating databases optimized for performance, implementing schema changes, and maintaining data architecture standards across all of the business’s databases.

• The Data Engineer leads innovation through exploration, benchmarking, making recommendations, and implementing big data technologies for platforms.

• Develop and implement scripts for database maintenance, monitoring, performance tuning, and so forth.

• Designing and developing scalable ETL packages (Abinitio) from the business source systems and the development of ETL routines in order to populate databases from sources and also to create aggregates.

• Oversee large-scale data Hadoop platforms and support the fast-growing data within the business.

• The Data Engineer is responsible for enabling and running data migrations across different databases and different servers, for example, data migration from SQL servers to Oracle.

• Define and implement data stores based on system requirements and other requirements.

• Perform thorough testing and validation in order to support the accuracy of data transformations and data verification used in machine learning models. Ensure proper data governance and quality across the Data and Analytics department and the business as a whole.

• The Data Engineer plays an analytical role where ad-hoc analyses of data stored in the business’s databases is performed and writes SQL scripts, stored procedures, functions, and views.

• Troubleshoot data issues within the business and across the business and presents solutions to these issues.

• Proactively analyse and evaluate the business’s databases in order to identify and recommend improvements and optimization.

• Analyse complex data elements and systems, data flow, dependencies, and relationships in order to contribute to conceptual physical and logical data models.

• Develop and implement scripts for database maintenance, monitoring, and performance tuning to be applied across the business.

• The Data Engineer also plays a supporting role to the data warehousing department in the implementation of the data warehouse for the new big data platforms. He/She works collaboratively with the entire Data and Analytics team, providing support to the entire department for its data centric needs.

• Keep up with industry trends and best practices, advising management on new and improved data engineering strategies that will drive departmental performance leading to improvement in overall data governance across the business, and promoting informed decision-making, ultimately improving overall business performance.

Technical skills:

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large, disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.

Experience and Related Skills

• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
• Experience with big data tools: Hadoop, Spark, Kafka, etc. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift, Abinitio
• Experience with stream-processing systems: Storm, Spark-Streaming,

etc.

• Experience with object-oriented/object function scripting languages:

Python, Java, C++, Scala, etc.

• The candidate must demonstrate experience working with large and complex data sets as well as experience analyzing volumes of data through basic Microsoft Excel functions, for example, macros and pivot tables. A candidate for this position will also have had experience working in internet technologies, for example, SaaS, IaaS, and PaaS.
• A suitable candidate will also have had experience in the creation and debugging of databases critical to the business’s mission. The candidate will have strong working and conceptual knowledge of building and maintaining physical and logical data models and experience with Tableau, Domo or other business intelligence tools.
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