Senior Data Engineer

Data Engineering Team @Heetch

Our team's values

• Move smart: We are data driven, and employ tools and best practices to ship code quickly and safely (continuous integration, code review, automated testing, etc)
• Distribute knowledge: We want to scale our engineering team to a point where our contributions do not stop at the company code base. We believe in the Open Source culture and communication with the outside world
• Leave code better than you found it: Because we constantly raise the bar
• Unity makes strength: Moving people from A to B is not as easy as it sounds but, we always keep calm and support each other
• Always improve: We value personal progress and want you to look back proudly on what you’ve done

What will be your role?

Does it sound like you?

• At least 3+ years in Software Engineering with a focus on Data Engineering
• Extensive experience with Spark or other cluster-computing frameworks
• Strong skills in Python + Scala or Java
• Advanced SQL query competencies (queries, SQL Engine, advanced performance tuning)
• Experience with Kafka in production
• Experience with workflow management tools (Airflow, Oozie, Azkaban, Luigi)
• Comfortable working directly with data analytics to bridge business requirements with data engineering
• Inventive and self-started

Bonus

• Experience designing and developing data warehouses
• Experience with data engineering in an AWS or cloud environment
• Performance tuning and administration of Spark, Kafka, Hive and Redshift
• Experience working with Dataiku
• Experience working with Kubernetes
• Experience deploying and managing AWS infrastructure
• Experience building data models for normalizing/standardizing varied datasets for machine learning/deep learning
• Experience working on a remote team
• Experience developing data engineering tools

What will you do?

• Implement and be responsible for a scalable data processing infrastructure which will evolve to based on business and engineering needs
• Build large-scale batch data pipelines
• Build large-scale real-time data pipelines
• Build and monitor ETL
• Be responsible for scaling up data processing flow to meet the rapid data growth at Heetch
• Consistently improve and evolve data model data schema based on business and engineering needs
• Implement systems tracking data quality and consistency
• Develop tools supporting self-service data pipeline management (ETL)
• Tune jobs to improve data processing performance
• Implement data and machine learning algorithms (A/B testing, Sessionization)
• Work with the business, product and engineering teams to create and implement a holistic data architecture
• Be involved in tech support 1 week per month from 8 am to 7 pm on weekends (compensated financially).