Senior Data Engineer

Job Description

Type: Full-time

About the Role

We are looking for a Senior Data Engineer to join Xeno and help us build a world-class data infrastructure to power our platform for omnichannel retailers. The ideal candidate is someone who thrives in a fast-paced startup environment, takes ownership of end-to-end projects, and is highly proficient in cost-efficient data engineering practices.

• Design, develop, and manage scalable ETL/ELT pipelines for ingesting, processing, and transforming large volumes of transactional and behavioral data.
• Utilize AWS DMS, DBT, and other AWS-native tools to build an efficient, cost-optimized data stack.
• Work hands-on with data lake solutions on S3 and explore tools like Snowflake and Databricks for advanced analytics.
• Build and maintain real-time streaming pipelines using tools like Apache Kafka, Kinesis, or Flink for event ingestion.
• Leverage Apache Hudi or similar frameworks for managing incremental data in the data lake.
• Utilize Athena, Redshift, or Presto for analytical queries and data transformations.
• Implement OLAP solutions and develop strategies for serving large-scale analytics.
• Build workflow orchestration systems with tools like Airflow or Step Functions to manage data pipeline dependencies and schedules.
• Guide and mentor junior developers or interns, sharing best practices and technical insights.
• Collaborate closely with product teams to align data solutions with business requirements.

• Core AWS Services: S3, Redshift, Glue, DMS, Lambda, Kinesis
• Data Modeling & Transformation: DBT, Athena, Presto
• Streaming & Processing: Apache Kafka, Flink
• Data Lake Management: Apache Hudi, Parquet, Avro
• Workflow Orchestration: Airflow, Step Functions
• Analytics Platforms: Snowflake, Databricks

What We're Looking For

• Hands-on experience in building and optimizing ETL/ELT pipelines at scale.
• Deep knowledge of AWS services, including but not limited to DMS, S3, Glue, Lambda, and Redshift.
• Strong experience with DBT for data transformation and modeling.
• Exposure to Snowflake or Databricks, with an understanding of their pros/cons and cost implications.
• Expertise in cost-effective data solutions leveraging raw AWS technologies.
• Experience working with real-time streaming systems like Kafka or Kinesis.
• Familiarity with Hudi, Parquet, or Avro for efficient storage and querying in a data lake.

• Demonstrated experience in leading and mentoring junior developers or interns.
• Strong individual contributor (IC) who can eventually transition into an Architect/Principal Engineer or team lead role.
• Proven ability to take on large, end-to-end projects, delivering on time and with high quality.

• Hardworking, relentless, and willing to take ownership of challenging problems.
• A problem-solver with a pragmatic approach to balancing scalability and cost-efficiency.
• A self-starter who thrives in small teams with a startup mindset.

• Be part of a growing team where your contributions directly impact the product and company growth.
• Opportunity to work with cutting-edge technologies and define the data architecture from the ground up.
• A clear career trajectory to technical leadership or people management based on your aspirations.
• Competitive salary and significant ESOPs to align incentives with the company's growth.