Data Engineer

• Data Engineer

The ideal candidate will have 5+ years of software and data engineering experience and will work closely with engineers, architects, product teams, analysts, and data scientists to design, build, and operate reliable, scalable data solutions.

Responsibilities

Design, build, and maintain scalable, low-latency batch and streaming data pipelines.

Develop data processing workflows using technologies such as Flink, Spark, Kafka, Snowflake, Iceberg, and Parquet.

Build and enhance ETL/ELT pipelines and reusable data engineering components.

Implement data models and optimize data processing and query performance.

Follow engineering best practices for testing, data quality, CI/CD, monitoring, and production reliability.

Troubleshoot pipeline failures, performance issues, and data quality problems.

Collaborate with senior engineers and architects on technical design and implementation decisions.

Evaluate and adopt new technologies and AI-assisted development tools where appropriate.

Support event-driven, behavioral analytics, personalization, and customer data use cases.

Minimum Qualifications

Bachelor s or master s degree in computer science, Engineering, or related technical field.

5+ years of hands-on software and data engineering experience .

Strong programming experience with Python and SQL.

Hands-on experience with big data technologies such as Kafka, Flink, Spark, Parquet, Iceberg, or Delta Lake.

Experience with Snowflake or similar cloud data platforms.

Strong understanding of data modeling, ETL/ELT, and scalable data processing.

Experience with batch and/or event-streaming architectures.

Experience building and supporting production data pipelines.

Familiarity with testing, CI/CD, monitoring, and observability practices.

Strong problem-solving and communication skills.

Preferred Qualifications

Experience with behavioral analytics, customer data platforms, or personalization use cases.

Experience with observability platforms such as Splunk, Dynatrace, or similar.

Exposure to large-scale data platform modernization or migration projects.

Familiarity with cloud platforms such as AWS.

Interest in modern data engineering technologies and AI-assisted engineering tools.

Ideal Candidate

Strong hands-on data engineer who can independently deliver well-designed production solutions.

Comfortable working with distributed data systems and modern cloud data technologies.

Collaborative and able to work effectively with engineers, architects, product teams, and stakeholders.

Focused on reliability, scalability, automation, and engineering quality.

Curious and continuously learning new data engineering technologies and practices.

Experience with Amplitude or similar product analytics platforms, including working with behavioral/event data, event taxonomy, user journeys, funnels, cohorts, and integrating analytics data into downstream data pipelines or warehouses.