Sr. Data Engineer
Budget: $250 – $750 USD
Data Engineer Job Responsibilities:
Develops and maintains scalable data pipelines and overall data platform architecture
Identifying and re-designing data infrastructure for greater scalability, optimizing data delivery, and automating manual processes
Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making
Designs multiple data integrations from multiple sources and different input formats
Implements processes and systems to monitor data quality, ensuring production data accuracy and availability
Performs data analysis required to troubleshoot data-related issues and assist in the resolution of data issues.
Works closely with a team of frontend and backend engineers, product managers, and analysts.
Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field. They should also have experience using the following software/tools:
Experience with big data tools: Hadoop, Spark, Kafka, Flink, Storm, etc
Experience with AWS cloud services: EMR, RDS, Redshift, Kinesis, Athena, etc
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Scala, Java, C++, or similar
Certified Data Analytics – Specialty or similar Data Engineer certification is a plus
- Data Engineering Tools
Apache Kafka, Apache Hadoop, Apache Cassandra, Apache Airflow
Develops and maintains scalable data pipelines and overall data platform architecture
Identifying and re-designing data infrastructure for greater scalability, optimizing data delivery, and automating manual processes
Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making
Designs multiple data integrations from multiple sources and different input formats
Implements processes and systems to monitor data quality, ensuring production data accuracy and availability
Performs data analysis required to troubleshoot data-related issues and assist in the resolution of data issues.
Works closely with a team of frontend and backend engineers, product managers, and analysts.
Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field. They should also have experience using the following software/tools:
Experience with big data tools: Hadoop, Spark, Kafka, Flink, Storm, etc
Experience with AWS cloud services: EMR, RDS, Redshift, Kinesis, Athena, etc
Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Scala, Java, C++, or similar
Certified Data Analytics – Specialty or similar Data Engineer certification is a plus
- Data Engineering Tools
Apache Kafka, Apache Hadoop, Apache Cassandra, Apache Airflow