AWS Data Engineer
Rakesh RakiUnited StatesMIDPosted 1h ago
SQLRelational databasesBig dataData pipelinesDashboardsReportsAnalytical modelsAWSS3EC2GlueEMRRDSRedshiftAthenaLambdaDynamoDBPythonRJavaC++ScalaNoSQL databasesOracleMS SQL ServerPostgresCassandraGitCI/CD pipelinesData modelingDimensional modelingData vaultStar/snowflake schemasAWS Glue Data CatalogData governanceData lineageData qualityREST APIHadoopSparkKafkaAzkabanLuigiAirflowInformaticaMuleSoftTalendTIBCOStormSpark-Streaming
About the Role
The Commonwealth of Pennsylvania is seeking a Data Engineer & Insights Analyst to join its analytics team, supporting the Pennsylvania Longitudinal Data System (PALDS). This role involves transforming complex data into actionable insights for state government agencies.
Key Responsibilities
• Transform complex data into trusted, usable information to support program delivery and executive decision-making
• Understand policy-relevant research questions and evaluate available data sources
• Develop analytics products to deliver actionable insights
• Perform root-cause analysis on internal and external data and processes
Requirements
• Advanced SQL knowledge and proficiency with relational databases
• Experience building and optimizing big data pipelines and architectures
• Advanced knowledge in designing, building, and refining dashboards, reports, and analytical models
• Experience working with student-level higher education data and establishing linkages to other sources
• Strong analytic skills related to working with unstructured datasets
• Experience with cloud-based data services such as AWS (S3, EC2, Glue, EMR, RDS, Redshift, Athena, Lambda, DynamoDB)
• Proficiency in object-oriented/object function scripting languages (Python, R, Java, C++, Scala)
• Experience with version control systems such as Git and CI/CD pipelines
• Knowledge of data modeling techniques including dimensional modeling, data vault, and star/snowflake schemas
• Familiarity with data cataloging and metadata management tools
• Understanding of data governance, data lineage, and data quality frameworks
• Knowledge of REST API design and integration patterns
• Experience with big data tools (Hadoop, Spark, Kafka)
• Experience with data pipeline and workflow management tools (Azkaban, Luigi, Airflow)
• Experience with data integration services solutions from vendors
• Experience with stream-processing systems (Storm, Spark-Streaming)