Job Description

About the Role

We are seeking an experienced Senior Data Engineer to design, build, and maintain modern, scalable data platforms and pipelines. In this role, you will partner with tech leads, solution architects, and clients to deliver high-performance, reliable, and cost-efficient data solutions that power analytics, business intelligence, and AI initiatives. You will also play a key role in mentoring junior engineers and driving engineering best practices across the team.

Key Responsibilities

Pipeline & Platform Development

Design, build, and optimize ETL/ELT pipelines using GCP services such as Dataflow, Dataproc, Composer (Airflow), Dataform, and Cloud Functions.
Develop both batch and streaming pipelines to handle structured, semi-structured, and unstructured data.

Data Modeling & Governance

Implement scalable data models in BigQuery to support analytics, BI reporting, and machine learning workloads.
Apply data governance frameworks, quality checks, and metadata management practices to ensure trusted and compliant data.

Optimization & Reliability

Optimize queries, pipeline performance, and storage costs while ensuring platform scalability, reliability, and fault tolerance.
Monitor, troubleshoot, and tune pipelines for continuous improvement.

Migration & Integration

Lead data migration projects from on-premises systems (e.g., Oracle, MicroStrategy) to modern cloud environments.
Integrate data from multiple sources, including APIs, databases, and event streams, into unified data platforms.

Collaboration & Leadership

Work closely with analysts, BI developers, and business teams to enable self-service analytics and faster decision-making.
Mentor and coach junior engineers, setting coding standards, reviewing designs, and sharing best practices.

Requirements

Experience

More than 5 years of experience in data engineering, with at least 2 years on Google Cloud Platform (GCP).
Proven track record in building and scaling cloud-native data platforms and pipelines.

Technical Skills

Strong SQL and Python skills for data transformation, automation, and pipeline orchestration.
Hands-on expertise with the GCP Data Stack (BigQuery, Dataflow, Dataproc, Composer, Dataform).
Experience with workflow orchestration (Airflow/Composer) and CI/CD for data pipelines.
Familiarity with modern data modeling concepts (relational, dimensional, and schema-on-read approaches).

Nice to Have

Exposure to Azure Data Stack (Synapse, Data Factory, Databricks, Logic Apps).
Knowledge of data governance, metadata management, and security best practices.

Soft Skills

Strong problem-solving, analytical, and communication skills.
Ability to balance technical depth with business impact, influencing both engineering teams and business stakeholders.