Data Engineer

Softility; Hyderabad; On-site; INR 1,200,000 - 1,600,000; Full time

Job summary

Softility seeks a Data Engineer with strong DevOps and analytical skills in Hyderabad. The role focuses on designing, building, and maintaining scalable ETL/ELT pipelines for financial datasets. Candidates should have a Master's degree in a relevant field and 3–5 years of data engineering experience. Proficiency in SQL, Python, cloud platforms, and DevOps tools is essential. Enjoy collaborating with teams and optimizing data quality and performance in a fast-paced environment.

Qualifications

• 3–5 years of hands-on experience in data engineering.
• Understanding of financial datasets and domain concepts.
• Knowledge of data quality/observability tools.

Responsibilities

• Build and maintain ETL/ELT pipelines for financial datasets.
• Develop data pipelines and optimized structures for analytics and reporting.
• Ensure data quality, lineage, and governance across platforms.
• Collaborate with Engineering, Operations and Analytics teams to support reporting and insights.
• Optimize pipeline performance and resource usage for cost optimization.

Skills

SQL

Python

DevOps tools (Git, CI/CD)

orchestration tools (Airflow, Pentaho)

cloud data platforms (Spanner, BigQuery, Redshift)

Education

Masters degree in computer science, Data Engineering, Information Systems

Tools

Terraform/IaC

Job description

Employment Type:
Full-time

Experience:
4-7 Years

Overview

Data Engineer with strong DevOps and analytical skills to design, build, and maintain scalable data pipelines for financial data. This role supports Engineering, Operations and analytics teams by delivering high-quality, reliable datasets and automated workflows.

Key Responsibilities

• Build and maintain ETL/ELT pipelines for financial datasets.
• Develop data pipelines and optimized structures for analytics and reporting.
• infrastructure-as-code, and pipeline monitoring (DevOps/DataOps).
• Ensure data quality, lineage, and governance across platforms.
• Collaborate with Engineering, Operations and Analytics teams to support reporting and insights.
• Optimize pipeline performance, reliability, and cloud resource usage for cost optimization.

Required Qualifications

• Masters degree in computer science, Data Engineering, Information Systems, or related field.
• 3–5 years of hands‑on experience in data engineering.
• Strong SQL and Python; experience with Spark or equivalent.
• Experience with cloud data platforms (Spanner, BigQuery, Redshift, or similar).
• Proficiency with DevOps tools (Git, CI/CD pipelines, Terraform/IaC).
• Experience with orchestration tools (Airflow, Pentaho).
• Understanding of financial datasets and domain concepts.
• Knowledge of data quality/observability tools.