Job Description
We are seeking a highly skilled and experienced Senior Data Engineer to lead the design, development, and optimization of our data infrastructure and pipelines. In this role, you will play a critical part in shaping the data architecture that supports our analytics, machine learning, and product development initiatives. You will work closely with data scientists, analysts, software engineers, and business stakeholders to ensure robust, scalable, and efficient data solutions across the organization.
The ideal candidate is a hands-on engineer with deep experience in data architecture, big data processing, and cloud-based infrastructure, along with a passion for mentoring and driving data best practices.
Work-Type: Hybrid, Expected Hours: 40 hours per week, Start: Feburary 2026
About the Role
Design, build, and maintain scalable and efficient data pipelines and ETL/ELT processes using tools like Apache Spark, Airflow, and Kafka
Architect and optimize data lakes and data warehouses (e.g., Snowflake, Redshift, BigQuery) to support analytics and machine learning workflows
Collaborate with cross-functional teams to understand business requirements and translate them into data engineering solutions
Ensure data quality, consistency, security, and compliance with governance standards
Lead efforts in data modeling, schema design, and data architecture best practices
Mentor junior data engineers and contribute to team development through code reviews and knowledge sharing
Work closely with DevOps teams to automate deployment, monitoring, and scaling of data infrastructure
Evaluate and implement emerging data technologies and architectures to improve performance and scalability
Troubleshoot complex data issues and optimize performance across the pipeline
Maintain comprehensive documentation of architecture, workflows, and technical decisions
Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field
5+ years of experience in data engineering or a similar role with a proven track record of delivering scalable data solutions
Expertise in Python, Scala, or Java for building data pipelines
Deep knowledge of SQL and experience with relational and NoSQL databases
Experience with big data technologies such as Apache Spark, Hadoop, Hive, Presto, or similar frameworks
Strong knowledge of cloud platforms like AWS, GCP, or Azure (e.g., S3, EMR, Glue, Lambda, BigQuery)
Hands-on experience with streaming data platforms (e.g., Kafka, Kinesis, Flink)
Familiarity with CI/CD workflows and infrastructure-as-code tools like Terraform or CloudFormation
Understanding of data security, privacy, and governance frameworks
Excellent communication skills and the ability to collaborate across technical and non-technical teams
Proven leadership experience and the ability to mentor, guide, and influence engineering teams