We are looking for a savvy Senior Data Engineer to join our growing team of analytics experts. The person will be responsible for initiating and expend our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional areas.
The candidate should be experienced in data pipeline building and data wrangler who enjoys optimizing data systems and building them from the ground up. Data Engineer will work closely with our software developers, database architects, data analysts, and data scientists team on all 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/squads. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
- Create and maintain optimal data pipeline architecture for our regional data ecosystem
- Assemble large, complex data sets that meet functional and non-functional business requirements
- Build data pipelines that clean, transform, and aggregate data from all disparate sources
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies
- Joining analytics and data science squad to build 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 Owner, Data, and UI/UX teams to assist with data-related technical issues and support their data infrastructure needs
- Keep our data secure across all boundaries through multiple AWS regions
- Be an advocate for best practices and continued learning and manage the team of 4-5 data analysts and data engineers
- Advanced working SQL and Python knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing data pipelines, architectures, and data sets including relational, non-relational data structures, file system, stream, and sensor data handling.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
- A successful project performing tasks in manipulating, processing, and extracting value from large disconnected datasets.
- Knowledge in Data Warehousing domain, good exposure to different data modelling techniques
- Familiar with Agile methologies
- 3+ years of experience in a Data Engineer or related role. They should also have experience using the following software/tools:
- Experience with big data tools: Spark, Kafka
- Experience with relational SQL and NoSQL databases, including Postgres, MariaDB
- Experience with data pipeline and workflow management tools i.e. Airflow, AWS Glue
- Experience with AWS cloud services: EC2, S3, RDS, Redshift
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