DevOps • Outsourced Product Engineering • Machine Learning • Infrastructure Automation • Software Engineering
201 - 500
August 10
Airflow
Amazon Redshift
Apache
AWS
Azure
Cloud
ETL
Google Cloud Platform
Hadoop
IoT
Java
Kafka
Numpy
Pandas
Python
Scala
Spark
Go
DevOps • Outsourced Product Engineering • Machine Learning • Infrastructure Automation • Software Engineering
201 - 500
• Design and build scalable data infrastructure with efficiency, reliability, and consistency to meet rapidly growing data needs • Build the applications required for optimal extraction, cleaning, transformation, and loading data from disparate data sources and formats using the latest big data technologies • Building ETL/ELT pipelines and work with other data infrastructure components, like Data Lakes, Data Warehouses and BI/reporting/analytics tools • Work with various cloud services like AWS, GCP, Azure to implement highly available, horizontally scalable data processing and storage systems and automate manual processes and workflows • Implement processes and systems to monitor data quality, to ensure data is always accurate, reliable, and available for the stakeholders and other business processes that depend on it • Work closely with different business units and engineering teams to develop a long-term data platform architecture strategy and thus foster data-driven decision-making practices across the organization • Help establish and maintain a high level of operational excellence in data engineering • Evaluate, integrate, and build tools to accelerate Data Engineering, Data Science, Business Intelligence, Reporting, and Analytics as needed • Focus on building test-driven development by writing unit/integration tests • Contribute to design documents and engineering wiki
• 1+ years of data engineering or equivalent knowledge and ability • 1+ years software engineering or equivalent knowledge and ability • Strong proficiency in at least one of the following programming languages: Python, Scala, or Java • Experience designing and maintaining at least one type of database (Object Store, Columnar, In-memory, Relational, Tabular, Key-Value Store, Triple-store, Tuple-store, Graph, and other related database types) • Good understanding of star/snowflake schema designs • Extensive experience working with big data technologies like Spark, Hadoop, Hive • Experience building ETL/ELT pipelines and working on other data infrastructure components like BI/reporting/analytics tools • Experience working with workflow orchestration tools like Apache Airflow, Oozie, Azkaban, NiFi, Airbyte, etc. • Experience building production-grade data backup/restore strategies and disaster recovery solutions • Hands-on experience with implementing batch and stream data processing applications using technologies like AWS DMS, Apache Flink, Apache Spark, AWS Kinesis, Kafka, etc. • Knowledge of best practices in developing and deploying applications that are highly available and scalable • Experience with or knowledge of Agile Software Development methodologies • Excellent problem-solving and troubleshooting skills • Process-oriented with excellent documentation skills
• Autonomous and empowered work culture encouraging ownership and growth quickly • Flat hierarchy with fast decision making • Strong, fun & positive environment with regular celebrations of success • Inclusive, diverse & authentic environment
Apply NowAugust 8
201 - 500
Build AI-powered products and solutions for HighLevel's marketing and sales platform.