Data Engineer

Miles helps foster greener travel and rewards you for it. We've built a great product that's simple, engaging, and tailored to each user. Join now to have the biggest impact while we're small and growing fast. You will be working with a great team from diverse backgrounds in a collaborative and supportive environment. We solve a wide variety of interesting technical challenges, and continually build up our platform to power the next generation of scale and features. We partner closely with Product, Design, and UX teams to build and ship the most impactful Responsibilities: - Work with product managers and data analysts to build data products that power our business. - Build and maintain data analytics reports, ETL pipelines, data lakes, and streaming solutions. - Analyze new data sources and work with stakeholders to understand the impact of integrating new data into existing pipelines and models - Develop & maintain critical data pipelines, using tools such as Apache Airflow, to ensure highly accurate and reliable business reporting - Perform ad-hoc analysis and provide insights to stakeholders within the organization such as Marketing, Growth & Sales teams to drive prioritization. - Create data visualizations and analytic reports using various tools such as Tableau, Databox, etc - Optimize database queries to improve and maintain performance on very large data sets. - Work closely with the business and data science team for the deliverables.

• Competitive salary based on experience - Opportunity to create impact in a high growth startup environment - Employee healthcare benefits includes medical, dental, vision insurance - Paid time off - Employee Referral bonus - Monthly team-building activities and happy hours - Stock in an early-stage fast-growing startup company

• 5+ years of relevant experience. Masters or Bachelors degree in CS/ML/AI or equivalent discipline. - Experience with building stream-processing systems, using solutions such as Kinesis, Kafka, Storm or Spark-Streaming. - Expertise with coding with Pyspark, Pandas, Scipy and visualizations with Tableau & Databox. Scheduling/orchestrating pipelines using Databricks and Airflow. - Expertise with data querying (SQL, Redshift, Spark) and analyzing billions of rows of data points. - Familiarity with SQL, especially within cloud-based data warehouses like Snowflake, Google BigQuery, and Amazon Redshift - Strong understanding of relational DB such as MySQL/PostgreSQL, document-based storage systems such as MongoDB or CouchDB, key-value stores (Memcached, Redis), Column-oriented stores (HBase, Cassandra), graph-oriented stores; their distinct advantages, disadvantages, and trade-offs. - Experience building machine learning, statistical, and analytical model, and tuning parameters. - Experience designing experiments and extracting insights. - Knowledge of various ETL techniques and frameworks. Bonus Points: - You have worked extensively with location and trips data at scale. - Specialization in spatiotemporal clustering in the presence of noise. - Worked on a successful product that has touched millions of consumers.