Senior Data Engineer

Prescience Decision Solutions (A Movate Company); Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Insurance plans

Collaborative environment

Learning and growth opportunities

Positive work culture

Job summary

Prescience Decision Solutions (A Movate Company) is seeking a seasoned Data Engineer to own end-to-end data pipelines in a Bengaluru-based role. You will design scalable architectures, ensure data quality, and govern data lineage across regulated domains using Python and SQL.

Ideal candidates have 6+ years in data engineering, with experience in Airflow, Hive/Hadoop, and modern data modeling concepts. Strong collaboration with finance and risk teams and adherence to CI/CD practices are expected.

Qualifications

• 6+ years of experience in Data Engineering.
• Strong data architecture and system design skills with sound trade-offs around data modeling, partitioning, and scalability.
• End-to-end ownership of production data pipelines, including design, deployment, monitoring, and operational support.
• Expertise in Python and SQL as primary tools; experience with Hive/Hadoop is a plus.
• Strong focus on data quality, validation, reconciliation, anomaly detection, and audit ability.

Responsibilities

• Design, build and maintain production data pipelines with reliability and scalability.
• Monitor, optimize and provide operational support for data workflows.
• Collaborate with finance, risk, and compliance domains requiring strong data lineage and governance.
• Develop and optimize transaction and fact tables; implement medallion architecture where applicable.

Skills

Data Engineering

Python

SQL

Data Modeling

Airflow

Hive/Hadoop

Data Governance

SQLAlchemy & Pandas

Tools

Hive

Hadoop

Airflow

MySQL

PostgreSQL

Spark

CI/CD

Job description

• 6+ years of experience in Data Engineering.
  
• Strong data architecture and system design skills with the ability to make sound trade-offs around data modeling, partitioning, and scalability.
  
• Demonstrated end-to-end ownership of production data pipelines, including design, deployment, monitoring, and operational support.
  
• Expertise in Python and SQL as primary tools; experience with Hive/Hadoop is a plus.
  
• Strong focus on data quality, validation, reconciliation, anomaly detection, and audit ability.
  
• Experience working with finance, risk, compliance, or other highly regulated data domains requiring strong data lineage and governance.
  
• Proven experience designing and building transaction and fact tables.
  
• Advanced SQL skills, including window functions, CTEs, CASE statements, and working across MySQL/PostgreSQL environments.
  
• Strong Python expertise, including pandas, SQLAlchemy, type hints, data classes, and object-oriented pipeline development.
  
• Experience with workflow orchestration platforms such as Airflow or similar tools.
  
• Strong understanding of data modeling concepts including fact/dimension modeling, normalization, and medallion architecture.
  
• Experience with YAML-based configurations, CI/CD practices, and Git-based development workflows.
  

Job Description:

• 6+ years of experience in Data Engineering.
  
• Strong data architecture and system design skills with the ability to make sound trade-offs around data modeling, partitioning, and scalability.
  
• Demonstrated end-to-end ownership of production data pipelines, including design, deployment, monitoring, and operational support.
  
• Expertise in Python and SQL as primary tools; experience with Hive/Hadoop is a plus.
  
• Strong focus on data quality, validation, reconciliation, anomaly detection, and audit ability.
  
• Experience working with finance, risk, compliance, or other highly regulated data domains requiring strong data lineage and governance.
  
• Proven experience designing and building transaction and fact tables.
  
• Advanced SQL skills, including window functions, CTEs, CASE statements, and working across MySQL/PostgreSQL environments.
  
• Strong Python expertise, including pandas, SQLAlchemy, type hints, data classes, and object-oriented pipeline development.
  
• Experience with workflow orchestration platforms such as Airflow or similar tools.
  
• Strong understanding of data modeling concepts including fact/dimension modeling, normalization, and medallion architecture.
  
• Experience with YAML-based configurations, CI/CD practices, and Git-based development workflows.
  

Requirements

Strongly Preferred:

• Experience with enterprise data platforms, internal data tooling ecosystems, metadata/catalog solutions, secrets management tools, developer productivity platforms, and ETL orchestration frameworks.
  

Nice-to-Have:

• Experience with Hive, Hadoop, Spark, or related big data technologies.
  

Benefits

• · Competitive salary and performance-based bonuses.
• · Comprehensive insurance plans.
• · Collaborative and supportive work environment.
• · Chance to learn and grow with a talented team.
• · A positive and fun work environment.