Jobs → Data & Analytics → AWS Data Engineer

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)

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