Data Services Engineer

JD Analysis: Data Service Engineer

Role Summary:

A Data Service Engineer is expected to act as an individual contributor responsible for

designing, building, and maintaining data pipelines and integrations that support

enterprise applications. The role requires hands-on experience in Python, SQL, ETL tools,

and API-based integrations.

Core Responsibilities:

• Design, develop, and maintain robust, scalable data pipelines using Python and

SQL.

• Work on end-to-end integration of enterprise applications using RESTful APIs,

webhooks, or other middleware tools.

• Optimize ETL workflows and data transformation frameworks for performance and

reliability.

• Monitor and troubleshoot data flows and integrated services to ensure smooth

operations.

• Collaborate with application teams and stakeholders to understand data

requirements and build integration solutions accordingly.

• Ensure data quality, security, and governance standards are met across all

integrations.

Key Skills & Experience:

Skill Area Requirement

Experience ~5 years (4.56 years acceptable range), preferably in a product or

SaaS setup

Programming Strong with Python and SQL

Data Pipelines /

ETL

Solid experience in building pipelines using ETL frameworks or

tools (e.g., Apache Airflow, Informatica, Talend, etc.)

APIs & Integration Strong understanding of REST APIs, JSON/XML parsing,

integration tools (like MuleSoft, Dell Boomi, etc. if mentioned)

Databases Proficient with relational databases (PostgreSQL, MySQL, etc.)

and query tuning

Cloud Exposure

(Preferred)

Familiarity with cloud platforms (AWS/GCP/Azure) is a plus

Soft Skills Self-starter, excellent problem-solving ability, stakeholder

communication

Preferred Qualifications:

• Bachelors/Master’s degree in Computer Science, IT, or related field.

• Certifications in ETL, API integration, or cloud data services (optional but preferred).

• Prior experience in enterprise-scale application integration is highly desirable