Dice
Data Engineer - 10+ years (USC) ONLY
Dice, Newark, New Jersey, us, 07175
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Techtriad Team - T3, is seeking the following. Apply via Dice today!Data Engineer
Location:
Hybrid Newark, NJType:
Contract to HireHigh Level Requirements for the Role:
Data ingestion from various on-prem and cloud sourcesAbility to build ETL pipelines to transform raw data into a format suitable for analysis (hands-on experience working with ETL tools like AWS Glue, Informatica etc.) and orchestrate transformation (using Airflow, other DAG tools)Experience working with big data technologies and data formats (e.g., Parquet, Delta, Iceberg)Expertise in Python, Spark, and SQL programming languagesStrong experience working on cloud platforms (AWS, Azure)Proven track record of enterprise data modeling including building schemas for data warehousingKnowledge of real-time data streaming and real-time analyticsKnowledge of Microsoft suite of tools is desired (Power BI, Synapse suite of analytics tools, Azure Data Factory)Your Impact:
Data ingestion from various on-prem and cloud sources, optimize data for large data processingBuild ETL pipelines to collect, blend, transform raw data into suitable formats for analysis (hands-on experience working with ETL tools like AWS Glue, Informatica etc.) and orchestrate transformation (using Airflow, other DAG tools)Create enterprise data models and define standards for data warehouse management adhering to data model definitionsInteract with data analytics and reporting teams to understand how data needs to be structured for consumptionConfigure and maintain MDM tools and system processes to ensure proper function of MDM mechanismsDefine master data quality validation criteria and implement automatic error detection schemesImplement data lineage capability to understand data movement across the enterpriseImplement data governance and standards including data definitions, data quality rules, data lineage, business glossary functionsSupport domain owners and data stewards to analyze quality issue root causes and remediation effortsMonitor cross-BU data provisioning to ensure provisioning is done via official sourcesYour Skills and Experience:
Bachelor's degree is required in a relevant field6+ years of experience working in a data engineering role supporting an on-prem Data Lake; experience within institutional asset management is a plus4+ years of strong experience with working on cloud platforms (AWS, Azure) (CloudFormation Templates, IAM, Aurora, EventBridge, Lambda, CloudWatch)2+ years of experience with Snowflake (SnowSQL, SnowPark)5+ years of experience with any relational database (SQL, Stored procedures, functions)5+ years of experience with Python, Spark, and SQL programming languagesExtensive hands-on experience in modern data lake architecture, database development, and data modelingKnowledge of real-time data streaming and real-time analyticsKnowledge of Microsoft suite of tools is desired (Power BI, Synapse suite of analytics tools, Azure Data Factory)Strong implementation skills and working knowledge of data structures, algorithms, and big data tools (Spark, Hadoop, Python, SQL, NoSQL, Hive); Must have hands-on experience using SparkSolid Linux OS and Shell Scripting experienceExperience working with big data technologies and data formats (e.g., Parquet, Delta, Iceberg)Extensive experience with at least one of the following RDMS: Oracle, SQL Server, Postgres, or MySQLStrong communication skills: able to partner with technical and business stakeholders to drive innovative solutionsPrior experience using data governance technology toolsPrior experience in a lead role is desired but not requiredExperience working in an agile environment embracing collaboration within and across teamsExcellent written and verbal communication skillsDetail-oriented; Analytical with strong problem-solving abilitiesProfessional and energetic self-starter. Comfortable with ambiguity, able to effectively take the conceptual to the pragmatic
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Location:
Hybrid Newark, NJType:
Contract to HireHigh Level Requirements for the Role:
Data ingestion from various on-prem and cloud sourcesAbility to build ETL pipelines to transform raw data into a format suitable for analysis (hands-on experience working with ETL tools like AWS Glue, Informatica etc.) and orchestrate transformation (using Airflow, other DAG tools)Experience working with big data technologies and data formats (e.g., Parquet, Delta, Iceberg)Expertise in Python, Spark, and SQL programming languagesStrong experience working on cloud platforms (AWS, Azure)Proven track record of enterprise data modeling including building schemas for data warehousingKnowledge of real-time data streaming and real-time analyticsKnowledge of Microsoft suite of tools is desired (Power BI, Synapse suite of analytics tools, Azure Data Factory)Your Impact:
Data ingestion from various on-prem and cloud sources, optimize data for large data processingBuild ETL pipelines to collect, blend, transform raw data into suitable formats for analysis (hands-on experience working with ETL tools like AWS Glue, Informatica etc.) and orchestrate transformation (using Airflow, other DAG tools)Create enterprise data models and define standards for data warehouse management adhering to data model definitionsInteract with data analytics and reporting teams to understand how data needs to be structured for consumptionConfigure and maintain MDM tools and system processes to ensure proper function of MDM mechanismsDefine master data quality validation criteria and implement automatic error detection schemesImplement data lineage capability to understand data movement across the enterpriseImplement data governance and standards including data definitions, data quality rules, data lineage, business glossary functionsSupport domain owners and data stewards to analyze quality issue root causes and remediation effortsMonitor cross-BU data provisioning to ensure provisioning is done via official sourcesYour Skills and Experience:
Bachelor's degree is required in a relevant field6+ years of experience working in a data engineering role supporting an on-prem Data Lake; experience within institutional asset management is a plus4+ years of strong experience with working on cloud platforms (AWS, Azure) (CloudFormation Templates, IAM, Aurora, EventBridge, Lambda, CloudWatch)2+ years of experience with Snowflake (SnowSQL, SnowPark)5+ years of experience with any relational database (SQL, Stored procedures, functions)5+ years of experience with Python, Spark, and SQL programming languagesExtensive hands-on experience in modern data lake architecture, database development, and data modelingKnowledge of real-time data streaming and real-time analyticsKnowledge of Microsoft suite of tools is desired (Power BI, Synapse suite of analytics tools, Azure Data Factory)Strong implementation skills and working knowledge of data structures, algorithms, and big data tools (Spark, Hadoop, Python, SQL, NoSQL, Hive); Must have hands-on experience using SparkSolid Linux OS and Shell Scripting experienceExperience working with big data technologies and data formats (e.g., Parquet, Delta, Iceberg)Extensive experience with at least one of the following RDMS: Oracle, SQL Server, Postgres, or MySQLStrong communication skills: able to partner with technical and business stakeholders to drive innovative solutionsPrior experience using data governance technology toolsPrior experience in a lead role is desired but not requiredExperience working in an agile environment embracing collaboration within and across teamsExcellent written and verbal communication skillsDetail-oriented; Analytical with strong problem-solving abilitiesProfessional and energetic self-starter. Comfortable with ambiguity, able to effectively take the conceptual to the pragmatic
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