About this role
Design and implement data warehouses and data lakes on AWS, leveraging semantic layers and BI integrations to enable governed data access for analytics.
Key Responsibilities
- Design and build AWS data pipelines
- Implement semantic layers with AtScale
- Govern data access and cataloging
- Integrate BI tools (Tableau/Power BI/QuickSight)
- Collaborate with distributed teams
Technical Overview
Hands-on AWS data & analytics stack including Lake Formation, Glue, Lambda, EMR, Kinesis, MWAA; data modeling, PySpark, SQL; BI integration with Tableau/Power BI/QuickSight; NoSQL databases.
Ideal Candidate
The ideal candidate is a senior data engineer specializing in AWS-based data lakes/lakehouses with AtScale and strong data governance, capable of leading distributed teams to build scalable data platforms for analytics.
Must-Have Skills
5+ years of experience designing and implementing data warehouses and data lakes/lakehouses on AWSHands-on experience with AtScale or similar semantic layer toolsProven success working with globally distributed teamsDeep working knowledge across AWS Data & Analytics servicesBuilding data lake architectures on Amazon S3Governance with AWS Lake FormationETL and metadata frameworks using AWS GlueAWS Lambda for serverless data processingAWS EMRAWS KinesisOrchestrating pipelines with AWS Step Functions/Amazon MWAARedshiftSpectrumServerless featuresAthenaRDS (PostgreSQLMySQLAurora)AWS DMSGlue ConnectorsEventBridgeSNSSQSSemantic modeling and BI tool integration (QuickSightTableauPower BI)Python and PySparkSolid SQL skills and performance tuningNoSQL databases such as DynamoDBMongoDBor DocumentDBPartitioningindexingscalingand data modelingArchitecting data pipelines using native AWS servicesData modeling concepts (dimensionalnormalizedlakehouse)
Nice-to-Have Skills
Experience in FSI / Retail / CPG domainsTerraform / IaCData virtualization (QuickSightPower BITableau) and data governance toolsAWS IAMSecrets ManagerCloudWatchCloudTrailKMSGenAI tools like GitHub CopilotData Mesh concepts
Tools & Platforms
Amazon Web ServicesAWSAmazon S3AWS Lake FormationAWS GlueAWS LambdaAmazon EMRAWS KinesisAWS Step FunctionsAmazon MWAAAmazon RedshiftAmazon AthenaAmazon RDSPostgreSQLMySQLAuroraDynamoDBMongoDBDocumentDBTableauPower BIQuickSight
Required Skills
AWSAmazon Web ServicesAtScalesemantic layerPythonPySparkSQLETLData WarehouseData LakeLakehouseAWS Lake FormationAWS GlueAWS LambdaAmazon RedshiftSpectrumServerlessAthenaRDSPostgreSQLMySQLAuroraDynamoDBMongoDBDocumentDBTableauPower BIQuickSight
Hard Skills
AWSAmazon Web ServicesAmazon S3AWS Lake FormationAWS GlueAWS LambdaAmazon EMRAWS KinesisAmazon MWAAAWS Step FunctionsAmazon RedshiftSpectrumServerlessAmazon AthenaAmazon RDSPostgreSQLMySQLAuroraDynamoDBMongoDBDocumentDBPythonPySparkSQLETLdata warehousedata lakelakehouseAtScalesemantic modelingTableauPower BIQuickSight
Soft Skills
CollaborationCommunicationMentoringDistributed teamsProblem-solvingDelivery-focused
Keywords for Your Resume
Amazon Web ServicesAWSAtScalesemantic layerPythonPySparkSQLETLData WarehouseData LakeLakehouseAWS Lake FormationAWS GlueAWS LambdaAmazon RedshiftAthenaRDSPostgreSQLMySQLDynamoDBMongoDBDocumentDBTableauPower BIQuickSightNoSQL databasesamazon web servicesawspysparkatscaledata lakedata warehouseredshiftathenardspythonsqletlquick sighttableau
Deal Breakers
No experience with AWS data & analytics services, Lack of hands-on data lake/warehouse design on AWS
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