Data Engineer-Pan India

Digile

India

On-site

INR 1,200,000 - 1,800,000

Full time

14 days+
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Job summary

Digile is seeking an experienced professional for a pivotal role in data migration and ETL development. Responsibilities include managing deliverables, collaborating with global teams, and preparing technical documentation. The ideal candidate has a Bachelor's degree in computer science, is proficient in SQL and Python, and has over 5 years of experience. The position requires strong analytical skills and the ability to manage large data volumes effectively. Additional skills in tools like Apache Airflow and database systems will be advantageous.

Qualifications

  • 5+ years of experience in ETL development or similar roles.
  • Proven expertise in managing large data volumes and diverse data sources.
  • Strong analytical skills in enterprise applications or integration projects.
  • Excellent communication skills for global collaboration.
  • Hands-on experience with industry standards and methodologies.

Responsibilities

  • Manage in-house and vendor deliverables to meet commitments.
  • Capture operational metrics and performance indicators.
  • Collaborate with globally distributed teams.
  • Travel to various locations as needed.
  • Prepare detailed technical documentation.
  • Design, code, and review solutions for quality.
  • Implement best practices for process improvements.
  • Report project performance metrics and KPIs.

Skills

SQL/PL-SQL
Python programming
Unix Shell Scripting
Analytical skills

Education

Bachelor’s degree in computer science or a related field

Tools

Apache Airflow
Oracle
MySQL
DB2
ServiceNow

Job description

Job Description

As a key member of the QTC, you will play a pivotal role in migrating data from diverse sources and applications, developing solutions, validating systems, and addressing various challenges in enterprise applications. You will be involved in the complete development lifecycle—from analysis and design to testing and release—focusing on delivering solutions that align with business goals, technical requirements, and best practices.

Key Responsibilities
  • Manage in-house and vendor deliverables effectively to meet time, scope, and budget commitments.
  • Capture operational metrics and performance indicators to highlight the value of team deliverables and enhance visibility into operations.
  • Collaborate with globally distributed teams to build strong working relationships across internal and external stakeholders.
  • Travel to various Equinix locations as needed; flexibility for travel is required.
  • Prepare detailed technical documentation for deliverables.
  • Design, code, and review solutions to ensure high standards of quality.
  • Identify, define, and implement best practices for process improvements within the SDLC framework.
  • Prepare and report project performance metrics and KPIs.
Qualifications & Experience
  • Bachelor’s degree in computer science or a related field with 5+ years of experience in ETL development or similar roles.
  • Proven expertise in managing large data volumes and working with diverse data sources.
  • Strong analytical skills with a track record of success in enterprise applications or integration projects.
  • Excellent communication skills to effectively collaborate with global teams.
  • Hands‑on experience using industry best practices for standards and methodologies.
Technical Skills (Must‑Have)
  • Proficiency in SQL/PL-SQL.
  • Advanced knowledge of Python programming.
  • Hands‑on experience with Unix Shell Scripting.
  • Strong analytical skills for data engineering tasks.
Technical Skills (Good‑to‑Have)
  • Familiarity with tools like Apache Airflow for data migration workflows.
  • Experience with database systems such as Oracle, MySQL, or DB2.
  • Knowledge of legacy data migration from diverse sources.
  • Previous experience with data migration to platforms like ServiceNow.
Additional Skills (Advantageous)
  • Familiarity with Siebel Complex assets data model.
  • Understanding of CI/CD pipelines using GitHub Actions.
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