Senior Data Engineer - (GCP & Lakehouse Architecture) - On Site - Octopus by RTG

We are seeking an experienced Senior Data Engineer to lead the design, development, and scaling of our next-generation, cloud-native Data Lakehouse platform on Google Cloud Platform (GCP). In this role, you will be instrumental in modernizing our data infrastructure, building robust ELT/ETL pipelines, and establishing enterprise-grade data modeling standards to empower analytics, machine learning, and business intelligence. If you are passionate about modern open-source table formats, high-performance distributed computing, and data reliability, we would love to have you on the team.

Key Responsibilities

• Lakehouse Architecture & Development: Design, deploy, and maintain a scalable GCP-based Lakehouse ecosystem leveraging Apache Iceberg for transactional consistency, time-travel, and efficient storage management.

• Pipeline Engineering: Architect, build, and optimize high-throughput ETL/ELT data pipelines using Python and Apache Airflow for orchestrating complex dependency workflows.

• Big Data Processing: Implement large-scale distributed data processing workloads and transformation pipelines using Apache Spark.

• Data Warehousing & Analytics: Leverage BigQuery for high-performance analytical queries, cost optimization, partition/cluster management, and serving structured data to downstream consumers.

• Transformation & Quality: Write clean, modular, and testable transformation code using dbt (Data Build Tool), embedding automated data testing, documentation,and lineage tracking.

•Data Modeling: Lead dimensional and semantic data modeling efforts (Star/Snowflake schemas, One-Big-Table, and Lakehouse medallion architectures) to ensure high query performance and seamless business usability.

• Performance Tuning & SQL Mastery: Write, optimize, and troubleshoot complex SQL queries to ensure low latency and cost-efficient processing across large datasets.

• Collaboration: Partner closely with data scientists, analytics teams, and product managers to understand data requirements and deliver robust, production-ready data products.

Requirements

•3+ years of hands-on experience designing and implementing enterprise-grade data platforms and pipelines.

• Cloud Platform: Proven production experience with Google Cloud Platform (GCP) core data services (BigQuery, Cloud Storage, Dataflow/Dataproc, IAM).

• Lakehouse & Table Formats: Deep understanding of modern lakehouse concepts and hands-on experience with Apache Iceberg.

• Transformation & Orchestration: Advanced proficiency in dbt for pipeline transformations and Apache Airflow for workflow orchestration.

• Big Data & Compute: Strong working knowledge of Apache Spark for distributed data processing.

• Programming & Querying:

o Advanced Python programming skills for data engineering tasks and custom operator development.

o Expert-level SQL writing and performance tuning capabilities.

• Data Modeling: Demonstrated expertise in dimensional modeling, data warehousing concepts, and schema design for analytical workloads.

• Methodologies: Strong grasp of modern ETL/ELT design patterns, CI/CD for data pipelines, data governance, and data quality best practices.