The Senior Data Engineer leads the design, development, and optimization of modern, scalable data platforms and pipelines. This role partners 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. The Senior Data Engineer also mentors junior engineers and drives engineering best practices across the team.
Key Responsibilitieso Design, build, and optimize ETL/ELT pipelines using GCP services such as Dataflow, Dataproc, Composer (Airflow), Dataform, and Cloud Functions.
o Develop both batch and streaming pipelines to handle structured, semi-structured, and unstructured data.
o Implement scalable data models in BigQuery to support analytics, BI reporting, and machine learning workloads.
o Apply data governance frameworks, quality checks, and metadata management practices to ensure trusted and compliant data.
o Optimize queries, pipeline performance, and storage costs while ensuring platform scalability, reliability, and fault tolerance.
o Monitor, troubleshoot, and tune pipelines for continuous improvement.
o Lead data migration projects from on-premises systems (e.g., Oracle, MicroStrategy) to modern cloud environments.
o Integrate data from multiple sources, including APIs, databases, and event streams, into unified data platforms.
o Work closely with analysts, BI developers, and business teams to enable self-service analytics and faster decision-making.
o Mentor and coach junior engineers, setting coding standards, reviewing designs, and sharing best practices.
RequirementsExperience
o More than 5 years of experience in data engineering, with at least 2 years on Google Cloud Platform (GCP).
o Proven track record in building and scaling cloud-native data platforms and pipelines.
o You are comfortable with Big Data, massively scalable databases, cloud infrastructures, and distributed algorithms.
o You have a passion for sustainable software development and have gathered several years of experience in technical roles.
o You have a good understanding of the capabilities in large public cloud environments and may have used resources from Amazon AWS, MS Azure, or Google's GCP.
Technical Skills
o Strong SQL and Python skills for data transformation, automation, and pipeline orchestration.
o Hands-on expertise with the GCP Data Stack (BigQuery, Dataflow, Dataproc, Composer, Dataform).
o Along with your expertise in Python and SQL, you have hands-on experience or a strong interest in technologies such as Hadoop, Apache Spark, Hive, Airflow, RDBMS, NoSQL, DevOps, Kubernetes, and Java or .NET
o Experience with workflow orchestration (Airflow/Composer) and CI/CD for data pipelines.
o Familiarity with modern data modeling concepts (relational, dimensional, and schema-on-read approaches).
Soft Skills
o Strong problem-solving, analytical, and communication skills.
o Ability to balance technical depth with business impact, influencing both engineering teams and business stakeholders.
Nice to Have
o Exposure to Azure Data Stack (Synapse, Data Factory, Databricks, Logic Apps).
o Knowledge of data governance, metadata management, and security best practices.
Preferred Qualificationso Bachelor's degree in Computer Science, Engineering, or related field.
o Google Cloud Professional Data Engineer or equivalent cloud certification (preferred).
o Experience contributing to AI/ML or Gen AI projects (nice to have).
o Fluent in English.