Job Description
Our proprietary software-as-a-service helps automotive dealerships and sales teams better understand and predict exactly which customers are ready to buy, the reasons why, and the key offers and incentives most likely to close the sale. Its micro-marketing engine then delivers the right message at the right time to those customers, ensuring higher conversion rates and a stronger ROI.
Key Responsibilities
You will be part of our data platform & product insights data engineering team. As part of this agile team, you will work in our cloud native environment to
Build & support data ingestion and processing pipelines. This will entail extract, load and transform of 'big data' from a wide variety of sources, both batch & streaming, using latest data frameworks and technologies
Build real-time monitoring dashboards and alerting systems.
Partner with product to assemble large, complex data sets that meet functional / non-functional business requirements, ensure build out of Data Dictionaries/data catalog and detailed documentation and knowledge around these data assets, metrics and KPIs.
Warehouse this data, build data marts, data aggregations, metrics, KPIs, business logic that leads to actionable insights into our product efficacy, marking platform, customer behaviour, retention etc.
Requirements & Experience
Strong knowledge of advanced SQL, data warehousing concepts, DataMart designing.
Having experience in in modern data platform components such as the Hadoop, Hive, Spark, Python, Scala, etc.
Experience with setting up and maintaining Data warehouse (Google BigQuery, Redshift, Snowflake) and Data Lakes (GCS, AWS S3 etc.) for an organization
Having strong experience in one of the Cloud providers - Azure, GCP, AWS.
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra / MongoDB.
Experience with data pipeline and workflow management tools: Airflow, Dataflow, Dataproc etc.
Experience with Distributed Versioning Control environments such as GIT, Azure DevOps
Strong problem solving and communication skills.
Qualifications
Bachelors or Master's degree in Computer Science, Applied Mathematics or a related engineering discipline required.
3 to 6 years of experience in Big Data and Data Engineering.