We are seeking a highly motivated Data Engineer to design, build, and maintain scalable data platforms and pipelines that enable analytics, reporting, machine learning, and AI-driven business solutions. The ideal candidate will have expertise in data integration, cloud technologies, data warehousing, and modern data engineering practices, with a strong focus on data quality, performance, and reliability.

The Data Engineer will work closely with business stakeholders, data architects, analysts, data scientists, and application teams to deliver trusted and scalable data solutions.

Data Pipeline Development

Design, develop, and maintain scalable ETL/ELT data pipelines.
Build and optimize batch and real-time data ingestion frameworks.
Integrate data from multiple sources, including databases, APIs, SaaS applications, and third-party systems.
Ensure data consistency, quality, and reliability across platforms.

Data Platform Engineering

Develop and support enterprise Data Lake, Data Warehouse, and Lakehouse architectures.
Implement scalable data solutions on cloud platforms.
Design data models to support reporting, analytics, and AI/ML use cases.
Optimize data storage, processing, and query performance.

Data Quality & Governance

Establish data validation, cleansing, and monitoring processes.
Implement data governance, lineage, cataloging, and metadata management practices.
Ensure compliance with security, privacy, and regulatory requirements.
Support audit and data quality initiatives.

Performance Optimization

Monitor and tune data pipelines and databases for performance and scalability.
Identify and resolve data bottlenecks and processing issues.
Optimize SQL queries and large-scale data transformations.

Collaboration & Stakeholder Engagement

Collaborate with Data Architects to implement enterprise data solutions.
Work closely with BI developers, analysts, and data scientists to support analytical needs.
Participate in requirements gathering, solution design, and technical reviews.
Provide production support and troubleshooting for critical data platforms.

DevOps & Automation

Implement CI/CD pipelines for data engineering solutions.
Automate deployment, monitoring, and operational processes.
Support infrastructure-as-code and cloud automation initiatives.

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or related field.

Master's degree is a plus.

Experience

12+ years of experience in Data Engineering, Data Warehousing, or Big Data environments.
Experience building and supporting large-scale enterprise data platforms.
Experience working in Agile development environments.

Technical Skills

Programming Languages

Python

SQL

Java (Preferred)

Data Engineering Tools

Apache Spark

Databricks

dbt

Cloud Platforms

Microsoft Azure

AWS

Google Cloud Platform (GCP)

Data Platforms

Snowflake

Azure Synapse Analytics

Amazon Redshift

BigQuery

Teradata

Databases

SQL Server

Oracle

PostgreSQL

MySQL

MongoDB

Business Intelligence Tools

Tableau

Power BI

Looker

Qlik Sense

DevOps & Version Control

Git

Azure DevOps

Jenkins

Terraform

Docker

Kubernetes

Preferred Skills

Data Lakehouse Architecture

Real-Time Streaming Architecture

Data Mesh Concepts

Master Data Management (MDM)

Data Governance Frameworks

Machine Learning Data Pipelines

API Development & Integration

Event-Driven Architecture

Soft Skills

Strong analytical and problem-solving abilities.
Excellent communication and stakeholder management skills.
Ability to work independently and collaboratively within cross-functional teams.
Strong documentation and presentation skills.
Attention to detail and commitment to delivering high-quality solutions.

DE&A - Core - Cloud Data Engineering - Snowflake Data Engineering