Senior Data Engineer

Honda is seeking a highly skilled Senior Data Engineer to join its Data & Analytics team. The ideal candidate will play a key role in designing, building, and maintaining modern data platforms to support enterprise analytics, machine learning, and digital transformation initiatives. You will collaborate closely with business stakeholders, data scientists, and solution architects to enable data-driven decision-making across the organization.

Key Responsibilities

Design, build, and optimize large-scale data pipelines and ETL/ELT processes using modern data engineering tools and cloud technologies.

Develop and maintain scalable data architectures to support advanced analytics and reporting requirements.

Collaborate with cross-functional teams (data scientists, analysts, business units) to understand data needs and deliver reliable data solutions.

Ensure data quality, governance, and security across all data platforms.

Implement best practices for data ingestion, transformation, and storage in cloud and on-prem environments.

Monitor, troubleshoot, and improve performance of data systems.

Mentor junior engineers and contribute to the establishment of engineering standards and practices.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field.

6+ years of professional experience in data engineering, with proven expertise in large-scale data environments.

Strong proficiency in SQL, Python, and one or more data processing frameworks (e.g., PySpark, Spark, Hadoop).

Hands-on experience with cloud platforms (AWS, Azure, or GCP), particularly cloud-native data services (e.g., Databricks, Snowflake, Redshift, BigQuery, Synapse).

Experience with data pipeline orchestration tools (Airflow, ADF, Luigi, etc.).

Solid understanding of data warehousing concepts, dimensional modeling, and ETL/ELT design patterns.

Knowledge of data governance, security, and compliance best practices.

Excellent problem-solving and communication skills.

Preferred Skills

Experience in automotive/manufacturing industry or with IoT/connected vehicle data.

Familiarity with real-time data streaming technologies (Kafka, Kinesis, Event Hubs).

Exposure to MLOps pipelines and supporting data science workflows.

Knowledge of DevOps practices (CI/CD, infrastructure as code, containerization with Docker/Kubernetes).