Remote Data Engineer — Build Scalable Pipelines & Analytics

Discover your 100% YOU with MicroSourcing!

Position: Data Engineer

Location: Philippines

Work setup & shift: Remote

Why join MicroSourcing?

**You'll Have

**Competitive Rewards: Enjoy above-market compensation, healthcare coverage on day one, plus one or more dependents, paid time-off with cash conversion, group life insurance, and performance bonuses

A Collaborative Spirit: Contribute to a positive and engaging work environment by participating in company-sponsored events and activities.

Work-Life Harmony: Enjoy the balance between work and life that suits you with flexible work arrangements.

Career Growth: Take advantage of opportunities for continuous learning and career advancement.

Inclusive Teamwork: Be part of a team that celebrates diversity and fosters an inclusive culture.

**Your Role

**As a Data Engineer, you will:

Design, build, and maintain scalable data pipelines and ETL/ELT processes.

Develop and optimize data architectures to support analytics and business intelligence initiatives.

Integrate data from multiple sources, ensuring data quality, integrity, and reliability.

Collaborate with data analysts, data scientists, and stakeholders to translate business requirements into technical solutions.

Implement monitoring, validation, and performance tuning to ensure efficient data processing.

**What You Need

**Non-negotiables

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field

3+ years of experience in data engineering or related roles

Strong proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server)

Hands-on experience with data processing frameworks and tools (e.g., Spark, Airflow, dbt, or similar)

Proficiency in at least one programming language such as Python, Java, or Scala

**Preferred Skills/expertise

**Experience working with cloud data platforms such as AWS, Azure, or GCP

Familiarity with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery)

Understanding of data modeling concepts (e.g., star schema, dimensional modeling)

Experience with streaming technologies (e.g., Kafka)