Data Engineer

Talkpush; Taguig; Hybrid; PHP 600,000 - 900,000; Full time

Benefits offered by this job

15% Night differential

20 PTO per year

Annual Appraisal

Annual Incentive

Hybrid Work Arrangement

HMO with FREE dependents

Group life insurance

Job summary

Talkpush is seeking a Data Engineer to design, develop, and implement data warehouse solutions. You will work with cloud-based technologies like Google BigQuery and SQL to build data pipelines and analytics that support clinical, hospital performance, and corporate functions.

The role emphasizes building scalable data pipelines, collaborating with cross-functional teams, and contributing to a high-energy healthcare data environment through CI/CD deployment and performance optimization.

Qualifications

• Bachelor’s degree in technology-related field or equivalent combination of education, training, and experience.
• Ability to build and optimize data sets and big data pipelines.
• Ability to perform root cause analysis on processes and data to identify improvements.
• Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata.
• Strong SQL and relational database design/development skills.
• Experience with cloud-based data warehouses such as Google BigQuery or equivalent.
• Familiarity with Scala, Java, and Python.
• Understanding of big data tools like Kafka, Spark, and workflow tools such as Airflow.

Responsibilities

• Assembling data sets that meet functional and non-functional requirements.
• Building data pipelines for extraction, transformation, and loading using GCP and SQL.
• Creating analytical tools to derive insights from data pipelines.
• Collaborating with data, design, and product teams to resolve data-related issues.
• Participating in testing and change control for production deployments.
• Designing, developing, reviewing, testing, and deploying with CI/CD for data warehouse solutions.
• Identifying data integrity issues and opportunities for process improvements.
• Monitoring performance and optimizing query execution plans.

Skills

SQL

Relational DB design

Big Data pipelines

Python/Scala/Java

Airflow

Kafka

Spark

Education

Bachelor’s degree in technology-related field

Tools

Google BigQuery

Airflow

Kafka

Spark

Job description

Work Arrangement:

• Night shift work schedule
• Hybrid work setup

Benefits:

• 15% Night differential
• 20 Paid Time Off (PTO) per year
• Annual Appraisal
• Annual Incentive
• Hybrid Work Arrangement
• HMO with FREE dependents
• Group life insurance

The Data Engineer is primarily responsible for participating in the design, development, and implementation of solutions for the data warehouse. The primary focus of the data warehouse includes data and analytics that support business operations including Clinical, Hospital Performance, and Corporate functions.

This role is cloud facing and requires knowledge in building and managing data engineering code in modern cloud-based technologies such as Google Big Query or equivalent. We are looking for a high energy individual willing to learn and evolve and would like to contribute to high impact healthcare environment.

Primary duties and responsibilities:

• Assembling small to medium complex sets of data that meet non-functional and functional business requirements
• Building required data pipelines for optimal extraction, transformation and loading of data from various data sources using GCP and SQL technologies
• Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics
• Working with stakeholders including data, design, and product teams and assisting them with data-related technical issues
• Participates in unit and system testing and follow existing change control processes for promoting solutions to production system, escalating issues as needed.
• Design, develop, review, test, and deploy using CI/CD to facilitate the data warehouse solutions.
• Identifies data integrity issues and analyzes data and process flows for process improvement opportunities.
• Monitoring system performance and evaluate query execution plans for improving overall system performance.
• Working with Integration Architect, develop, test and deploy the data pipelines.
• Participate in troubleshooting and maintaining existing solutions as required.

Qualifications:

• Bachelors’degree from an accredited college/university in technology related field or equivalent combination of education, training, and experience.
• Ability to build and optimize data sets, ‘big data’ data pipelines.
• Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions
• Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata
• Strong SQL and relational database design/development skills
• Development experience with cloud-based modern data warehouses such as Google Big Query or equivalent.
• Applicants should have a demonstrated understanding and experience ofrelational SQL databases including Big Query or equivalent, and function/object-oriented scripting languages including Scala, Java and Python.
• Applicants should also have an understanding of software and tools including big data tools like Kafka, Spark; workflow management tools such as Airflow.