Spark Engineer

As a Data Engineer at Caserta, you’ll work in small teams to deliver innovative solutions using core cloud data warehouse tools and Spark, Event Stream platforms, and other Big Data related technologies. In addition to building the next generation of data platforms, you’ll be working with some of the most forward-thinking organizations in data and analytics.

Responsibilities:

• Work as part of a team to develop ETL and ELT code in Python, Spark and PySpark for real-time data streaming
• Participate in development of cloud data warehouses and business intelligence solutions
• Data wrangling of heterogeneous data and explore and discover new insights
• Hands-on experience with new data platforms and programming languages (e.g. Python, Hive, Spark)

Qualifications:

  • Related work experience in Data Engineering or Data Warehousing
  • Proven experience with data warehousing, data ingestion, and data profiling
  • Proficient in Python and SQL
  • Strong aptitude for learning new technologies and analytics techniques
  • Highly self-motivated and able to work independently as well as in a team environment
  • Understanding of agile project approaches and methodologies
  • Optimizing the performance of business-critical queries and dealing with ETL job related issues
  • Building and migrating the complex ETL pipelines from Talend to redshift
  • Extracting and combining data from various heterogeneous data sources
  • Experience using Apache Spark
  • Strong communication – ability to explain complex technical issues in non-technical terms
  • Knowledge of database structures, theories, principles, and practices
  • Familiarity with implementing analytics solutions with one or more Hadoop distributions (Cloudera, Hortonworks, MapR, HDInsight, EMR)
  • Familiarity with streaming data ingestion
  • Consulting experience
  • Bachelor’s degree in Computer Science or a closely related field required

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