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Syed AwaisSA
Looking for a job

Syed Awais

@syedawais

I build scalable cloud data platforms and reliable real-time pipelines across regulated industries.

United States
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What I'm looking for

I'm looking to lead scalable cloud data platform and architecture work, building governed, reliable batch and real-time pipelines while mentoring teams and supporting analytics and AI/ML use cases.

At Alizatech, I lead data engineering initiatives across healthcare, FinTech, banking, and insurance, turning business requirements into scalable architectures, data products, and operational pipelines.

I build cloud lakehouse and warehouse platforms with AWS, Databricks, Delta Lake, Snowflake, Python, SQL, and PySpark. My work includes batch and real-time processing for clinical, claims, payments, transactions, policy, and underwriting data, with strong controls for governance, security, lineage, and PII/PHI protection.

Previously at Evolv and Molina Healthcare, I delivered Azure and Hadoop-based data solutions, dimensional models, Airflow workflows, Kafka pipelines, and governed reporting datasets. I also lead reviews, troubleshoot production systems, optimize Spark and SQL workloads, and mentor engineers on data quality and engineering standards.

Experience

Work history, roles, and key accomplishments

MH

Data Engineer

Molina Healthcare

Jul 2018 - May 2020 (1 year 10 months)

Built ingestion and transformation pipelines from relational databases, APIs, and healthcare sources for analytics and reporting. Used Hadoop, HDFS, Hive, and Spark for distributed processing and designed dimensional warehouse structures.

Education

Degrees, certifications, and relevant coursework

BS

Bachelor of Science in Computer Science

Bachelor of Science, Computer Science

Bachelor of Science in Computer Science.

Availability

Looking for a job

Location

United States

Authorized to work in

Salary expectations

110k+ USD

Skills

Data ArchitectureEnterprise Data PlatformLakehouseMedallion ArchitectureData ProductsAPIsReference ArchitectureIntegration PatternsDimensional ModelingPythonSQLPySparkScalaJavaBASHShell ScriptingPandasT SQLPl SQLREST APIsDatabricksDelta LakeUnity CatalogDatabricks WorkflowsDelta Live TablesSparkSpark SQLSpark Structured StreamingHadoopHDFSHiveMapReduceKafkaKafka Connect APIKafka StreamsAmazon KinesisAzure Event HubsAWSS3AWS GlueAmazon EMRAmazon RedshiftAmazon AthenaAWS LambdaAmazon RDSAWS DMSDynamoDBAWS IAMAWS Secrets ManagerAWS KMSCloudwatchAWS Step FunctionsAzureAzure Data FactoryAzure DatabricksADLS Gen2Azure SynapseGCPBigQueryGoogle Cloud StorageDataflowPub SubSnowflakeSnowpipeSnowflake StreamsSnowflake TasksSnowflake SnowparkPostgreSQLMySQLMS SQL ServerOracleTeradataMongoDBRedisETLELTBatch ProcessingReal time processingChange Data CaptureIncremental LoadData MigrationSFTPData ValidationReconciliationsAirflowDBTControl MKimball Modelling MethodologyStar SchemasDimensional Modeling (Star And Snowflake Schemas)Fact Dimension ModellingSCD Type 1SCD2Conformed DimensionsData MartsSemantic layerMetric LayerPower BITableauAmazon QuicksightData Quality FrameworkTestingMonitoringData LineageMetadata ManagementData CatalogsRBACAccess ControlEncryptionTokenizationPII ProtectionPHI ProtectionSecrets ManagementHIPAASOX and ITGC ComplianceGDPRAudit LoggingDockerKubernetesTerraformJenkinsGitHub ActionsAzure DevOpsGitCI CDTesting AutomationInfrastructure as CodeML Ready Dataset CreationFeature PipelinesFeature StoresMLFlowModel RegistryModel ServingVector DatabasesEmbeddingsRAG ArchitectureDocument Ingestion PipelinesKnowledge RepositoriesElectronic Health Records (EHR)EMRClinical DataHealthcare Claims DataHL7FHIREDI 837835SalesforceClaude CodeGitHub Co PilotCursorAI Assisted CodingAI Assisted Code ReviewAI Adoption

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