Senior Data Engineer | 6+ Years

ShimentoX Technologies; Bengaluru; On-site; INR 2,600,000 - 3,800,000; Full time

Job summary

ShimentoX Technologies in Bengaluru seeks a Senior Data Engineer to design, build, and own end-to-end production data pipelines, focusing on data architecture, system design, Python, and SQL.

You will implement Bronze/Silver/Gold architecture, ensure data quality and auditability, manage data models, and develop Airflow DAGs and Python ETL tooling. 6+ years of experience required.

Qualifications

• 6+ years of experience in Data Engineering.
• Strong Data Architecture and System Design skills.
• End-to-end production pipeline ownership.
• Expert SQL including Window Functions, CTEs, CASE logic.

Responsibilities

• Own data architecture and system design decisions for data pipelines and data models.
• Design and build scalable, production-grade data pipelines end-to-end.
• Design transaction-level fact tables and standard fact/dimension models.
• Implement Bronze/Silver/Gold (Medallion) architecture.
• Build pipelines for finance, risk, or compliance use cases where accuracy and auditability are critical.
• Implement data quality controls, reconciliation, anomaly detection, and audit trails.
• Write complex SQL using CTEs, window functions, CASE logic, COALESCE, NULLIF, and date/timestamp handling.
• Build idempotent data reload patterns and handle late-arriving or corrected records without double-counting.
• Develop and maintain Airflow-style DAGs and cross-pipeline dependencies.
• Build Python-based ETL tooling using Pandas, SQLAlchemy, and database drivers.
• Work with YAML-driven configurations and integrate with APIs where required.
• Own CI/CD processes using Git workflows.
• Document data models, pipeline logic, data lineage, and operational processes.

Skills

Data Architecture

System Design

Python

SQL

Data modeling

Data quality

Data lineage

Auditability

Production pipelines

Airflow

Pandas

SQLAlchemy

Database drivers

Tools

Airflow

Pandas

SQLAlchemy

MySQL

PostgreSQL

Job description

We are looking for a highly skilled Senior Data Engineer with strong expertise in Data Architecture, System Design, Python, and SQL to design, build, and own end-to-end production data pipelines powering analytics and business decision-making.

The ideal candidate should have strong experience in transaction-level data modeling, data quality, auditability, data lineage, and production pipeline ownership, preferably within finance, risk, or compliance data domains.

• Own data architecture and system design decisions for data pipelines and data models.
• Design and build scalable, production-grade data pipelines end-to-end.
• Design transaction-level fact tables and standard fact/dimension models.
• Implement Bronze/Silver/Gold (Medallion) architecture.
• Build pipelines for finance, risk, or compliance use cases where accuracy and auditability are critical.
• Implement data quality controls, reconciliation, anomaly detection, and audit trails.
• Write complex SQL using CTEs, window functions, CASE logic, COALESCE, NULLIF, and date/timestamp handling.
• Build idempotent data reload patterns and handle late-arriving or corrected records without double-counting.
• Develop and maintain Airflow-style DAGs and cross-pipeline dependencies.
• Build Python-based ETL tooling using Pandas, SQLAlchemy, and database drivers.
• Work with YAML-driven configurations and integrate with APIs where required.
• Own CI/CD processes using Git workflows.
• Document data models, pipeline logic, data lineage, and operational processes.

• 6+ years of experience in Data Engineering
• Strong Data Architecture and System Design skills
• End-to-end production pipeline ownership
• Expert SQL including Window Functions, CTEs, CASE logic
• Strong experience with MySQL / PostgreSQL
• Strong data quality, reconciliation, auditability, and lineage practices
• Experience with Airflow or similar orchestration tools
• Strong data modeling knowledge — Fact/Dimension, Normalization, Medallion Architecture

Good to Have

• Finance, Risk, or Compliance data experience
• Spark / Hive / Hadoop experience
• YAML-based pipeline configuration
• CI/CD and Git workflows
• Experience with large-scale production data platforms