Galaxy Holdings ★ 4.5

We build complex, mission-critical data platforms that power enterprise analytics, AI, and real-time operational systems. We are hiring Data Engineers across multiple seniority levels to design, build, and scale enterprise-grade data platforms. You will work on complex, high-volume, and highly regulated environments, building modern Data Lake, Data Warehouse, and Lakehouse architectures that enable advanced analytics and AI applications. Depending on experience, you may contribute as a hands-on Senior Engineer, lead architecture design as a Lead/Principal, or drive data platform strategy at a higher level.

Responsibilities:

Data Platform Development

• Design and develop scalable ETL/ELT pipelines (batch & real-time)

• Build and optimize enterprise Data Lake and Data Warehouse systems

• Develop data models (Star Schema, Snowflake, Data Vault where applicable)

• Ensure high data quality, consistency, and availability

Architecture & System Design (Lead/Principal level)

• Design enterprise Data Lakehouse architecture

• Define data integration patterns across banking and aviation systems

• Establish standards for data governance, lineage, metadata management

• Design scalable streaming systems (Kafka, Spark Streaming, etc.)

Performance & Optimization

• Optimize data storage, processing, and query performance

• Implement monitoring, logging, and observability for data pipelines

• Ensure compliance with security and regulatory standards (financial data, PII) Cross-Functional Collaboration

• Work closely with:

o AI / Data Science teams

o BI and Analytics teams o Core Banking / Financial Systems teams

• Support AI-ready data infrastructure

• Translate business requirements into scalable data solutions

Senior Data Engineer (4–6+ years)

• Strong hands-on experience building ETL/ELT pipelines

• Experience with Data Lake & Data Warehouse systems

• Proficient in SQL and Python / Scala

• Experience with Spark, Airflow, Kafka or equivalent tools

• Experience with at least one major cloud platform (AWS / GCP / Azure)

Lead Data Engineer (6–10+ years)

• Proven experience designing large-scale data architecture

• Experience leading technical initiatives or mentoring engineers

• Deep knowledge of distributed systems and data modeling

• Experience in complex domains (Core Banking, Payments, Aviation Ops)

Principal / Head-level Data Engineer (10+ years)

• Experience designing enterprise-wide Data Lakehouse platforms

• Strong knowledge of data governance, compliance, and security

• Experience leading large transformation programs

• Ability to align data strategy with business objectives

Technical Stack

• Languages: Python, Scala, SQL

• Big Data: Spark, Kafka, Flink

• Orchestration: Airflow

• Cloud: AWS / GCP / Azure

• Data Platforms: Snowflake, BigQuery, Redshift, Databricks

• Storage: S3 / ADLS / GCS

• DevOps & CI/CD practices

Education & Certifications (Highly Preferred)

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related fields

• MBA (Technology / Strategy) is an advantage for senior levels

• International certifications such as:

o AWS Certified Data Engineer / Data Analytics Specialty

o Google Professional Data Engineer

o Microsoft Azure Data Engineer Associate

o Databricks Certified Data Engineer

o CDMP (Certified Data Management Professional)

o TOGAF (for architecture-level candidates)

Core Competencies

• Strong analytical and system-thinking mindset

• Experience working with high-volume, mission-critical systems

• Understanding of financial and aviation data complexity

• Enterprise mindset: scalability, reliability, governance

• Strong collaboration and communication skills