Data Engineer

  • Sector: Monroe Insurance & Legal
  • Contact: Lou Angelica Castil
  • Client: Monroe Consulting Group
  • Location: City of Taguig
  • Salary: Negotiable
  • Expiry Date: 28 November 2023
  • Job Ref: BBBH426709_1700015291
  • Contact Email: lou.castil@monroeconsulting.com.ph

Executive search firm Monroe Consulting Group Philippines is recruiting on behalf of a leading homegrown financial services company, offering consumers technology-enabled solutions and a wide range of financial products and services. This insurance company is looking for Data Engineer who has experience in building and maintaining our data and data pipeline, as well as optimizing data flow and collection for cross functional components. The job is based in BGC, Taguig City, Philippines.

About the role:
The Data Engineer will be responsible building and maintaining our data and data pipeline, as well as optimizing data flow and collection for cross functional components. The ideal candidate 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 our software developers, data analysts and the business stakeholders 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 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. The Data Engineer will also create reports and dashboards as requested by business teams.

Key responsibilities include:

  • Create and maintain optimal data pipeline architecture
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • 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 'big data' technologies.
  • Build 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.
  • Create data tools for analytics and data analyst that assist them in building and optimizing our product into an innovative industry leader.
  • Work with data and analyst to strive for greater functionality in our data systems.
  • Build reports and dashboards to support the data needs of business teams.

Key requirements include:

  • 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.
  • Experience supporting and working with cross-functional teams in a dynamic environment.
  • 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
  • Experience with relational SQL and NoSQL databases, including Postgres, AWS Redshift and Dynamo DB
  • Experience with data pipeline and workflow management tools, including Airflow and Glue.
  • Experience with AWS cloud services: EC2, EMR, RDS, Redshift, DynamoDB, Airflow
  • Experience with stream-processing systems
  • Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
  • Experience in reporting tools, including Powerbi and Tableau
  • Experience with Snowflake is a plus.