Entry Level Enterprise Engineer Jobs
New grad enterprise engineer jobs welcome recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship work can matter more than a long resume. Most openings are on-site roles across Technology & Software, Energy, and Artificial Intelligence, with employers like Meter, Esri, and FanDuel hiring at this level now.
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INTRODUCTION
For over twenty-seven years RCR Technology Corporation has delivered the highest quality services to our clients with an expansive portfolio of industry-relevant services, and deep technical capabilities around data management and application development.
We are seeking a Senior Azure Data Engineer to help design, build, and operate our next-generation enterprise data platform on Microsoft Azure. You will own end-to-end delivery of data pipelines and data products that power analytics, regulatory reporting, operational dashboards, and emerging AI/ML use cases. You will partner closely with data architects, analytics engineers, data scientists, business stakeholders, and platform engineering teams to deliver reliable, performance, secure, and cost-efficient data solutions.
This role is ideal for an engineer with strong hands-on depth in Azure Data Factory, Azure Synapse Analytics and/or Databricks, and modern Lakehouse patterns, who is comfortable leading migration programs (e.g., Informatica-to-ADF, on-prem warehouse-to-cloud), mentoring mid-level engineers, and shaping engineering standards across the team.
KEY RESPONSIBILITIES
Pipeline Design & Development:
- Design and build robust, reusable, parameter-driven ingestion and transformation pipelines using Azure Data Factory, Synapse Pipelines, Data Bricks and/or Microsoft Fabric Data Factory.
- Implement medallion architecture (Bronze / Silver / Gold) on Azure Data Lake Storage Gen2 using Delta Lake, Parquet, and structured streaming patterns.
- Build performant ELT workflows that leverage pushdown to source systems (Synapse Dedicated SQL Pool, Azure SQL, Teradata) where appropriate.
- Develop and optimize PySpark notebooks and jobs on Azure Databricks or Synapse Spark.
Data Modeling & Warehousing:
- Design dimensional models (Kimball star/snowflake) and data vault patterns for analytics consumption.
- Implement Slowly Changing Dimensions (Type 1/2/3), Change Data Capture, and late-arriving data patterns.
- Tune distributed SQL workloads in Synapse Dedicated SQL Pool / Fabric Warehouse, including distribution keys, partitioning, and clustered column store indexes.
Platform Engineering & DevOps:
- Implement CI/CD for data pipelines using Azure DevOps (YAML pipelines, ARM/Bicep/Terraform) across Dev / SIT / UAT / Prod environments.
- Instrument pipelines with robust logging, auditing, and monitoring using Azure Monitor, Log Analytics, and KQL.
- Define and enforce coding standards, code review practices, branching strategies, and release management.
Migration & Modernization:
- Lead or contribute to legacy-to-cloud migrations — e.g., Informatica PowerCenter to Azure Data Factory, on-premises Teradata / Oracle / SQL Server to Synapse or Fabric.
- Perform workload assessment, capacity planning, and cost modeling for target-state architectures.
- Production incident response for critical pipelines.
REQUIRED QUALIFICATIONS
- Deep hands-on expertise with Azure Data Factory: pipelines, datasets, linked services, triggers, parameterization, mapping data flows, and all three Integration Runtime types (Azure, Self-hosted, SSIS).
- Strong Experience in Data Bricks and PySpark.
- Production experience with one or more of: Azure Synapse Analytics (Dedicated and Serverless SQL Pools, Spark Pools) OR Azure Databricks (Delta Lake, Unity Catalog) OR Microsoft Fabric (Warehouse, Lakehouse, OneLake).
- Strong working knowledge of Azure Data Lake Storage Gen2 (hierarchical namespace, RBAC + ACLs, lifecycle management, security).
- Experience with Azure Key Vault, Azure AD / Entra ID (including managed identities and service principals), and private networking (VNet integration, private endpoints).
- Monitoring and troubleshooting with Azure Monitor, Log Analytics, and KQL.
- Advanced SQL — window functions, CTEs, query optimization, execution plan analysis, performance tuning.
- Strong Python for data engineering — pandas, PySpark, REST API integration, unit testing (pytest).
- Proficient in T-SQL; familiarity with Spark SQL, KQL, PowerShell, and Bash shell scripting.
PREFERRED QUALIFICATIONS
- 5+ years of data warehouse development experience.
- 5+ years of data modeling experience using ERWIN or similar tools.
- 2+ years of experience with Azure Data Factory and Snowflake.
- Medicaid Domain Knowledge is a plus.
INTRODUCTION
For over twenty-seven years RCR Technology Corporation has delivered the highest quality services to our clients with an expansive portfolio of industry-relevant services, and deep technical capabilities around data management and application development.
We are seeking a Senior Azure Data Engineer to help design, build, and operate our next-generation enterprise data platform on Microsoft Azure. You will own end-to-end delivery of data pipelines and data products that power analytics, regulatory reporting, operational dashboards, and emerging AI/ML use cases. You will partner closely with data architects, analytics engineers, data scientists, business stakeholders, and platform engineering teams to deliver reliable, performance, secure, and cost-efficient data solutions.
This role is ideal for an engineer with strong hands-on depth in Azure Data Factory, Azure Synapse Analytics and/or Databricks, and modern Lakehouse patterns, who is comfortable leading migration programs (e.g., Informatica-to-ADF, on-prem warehouse-to-cloud), mentoring mid-level engineers, and shaping engineering standards across the team.
KEY RESPONSIBILITIES
Pipeline Design & Development:
- Design and build robust, reusable, parameter-driven ingestion and transformation pipelines using Azure Data Factory, Synapse Pipelines, Data Bricks and/or Microsoft Fabric Data Factory.
- Implement medallion architecture (Bronze / Silver / Gold) on Azure Data Lake Storage Gen2 using Delta Lake, Parquet, and structured streaming patterns.
- Build performant ELT workflows that leverage pushdown to source systems (Synapse Dedicated SQL Pool, Azure SQL, Teradata) where appropriate.
- Develop and optimize PySpark notebooks and jobs on Azure Databricks or Synapse Spark.
Data Modeling & Warehousing:
- Design dimensional models (Kimball star/snowflake) and data vault patterns for analytics consumption.
- Implement Slowly Changing Dimensions (Type 1/2/3), Change Data Capture, and late-arriving data patterns.
- Tune distributed SQL workloads in Synapse Dedicated SQL Pool / Fabric Warehouse, including distribution keys, partitioning, and clustered column store indexes.
Platform Engineering & DevOps:
- Implement CI/CD for data pipelines using Azure DevOps (YAML pipelines, ARM/Bicep/Terraform) across Dev / SIT / UAT / Prod environments.
- Instrument pipelines with robust logging, auditing, and monitoring using Azure Monitor, Log Analytics, and KQL.
- Define and enforce coding standards, code review practices, branching strategies, and release management.
Migration & Modernization:
- Lead or contribute to legacy-to-cloud migrations — e.g., Informatica PowerCenter to Azure Data Factory, on-premises Teradata / Oracle / SQL Server to Synapse or Fabric.
- Perform workload assessment, capacity planning, and cost modeling for target-state architectures.
- Production incident response for critical pipelines.
REQUIRED QUALIFICATIONS
- Deep hands-on expertise with Azure Data Factory: pipelines, datasets, linked services, triggers, parameterization, mapping data flows, and all three Integration Runtime types (Azure, Self-hosted, SSIS).
- Strong Experience in Data Bricks and PySpark.
- Production experience with one or more of: Azure Synapse Analytics (Dedicated and Serverless SQL Pools, Spark Pools) OR Azure Databricks (Delta Lake, Unity Catalog) OR Microsoft Fabric (Warehouse, Lakehouse, OneLake).
- Strong working knowledge of Azure Data Lake Storage Gen2 (hierarchical namespace, RBAC + ACLs, lifecycle management, security).
- Experience with Azure Key Vault, Azure AD / Entra ID (including managed identities and service principals), and private networking (VNet integration, private endpoints).
- Monitoring and troubleshooting with Azure Monitor, Log Analytics, and KQL.
- Advanced SQL — window functions, CTEs, query optimization, execution plan analysis, performance tuning.
- Strong Python for data engineering — pandas, PySpark, REST API integration, unit testing (pytest).
- Proficient in T-SQL; familiarity with Spark SQL, KQL, PowerShell, and Bash shell scripting.
PREFERRED QUALIFICATIONS
- 5+ years of data warehouse development experience.
- 5+ years of data modeling experience using ERWIN or similar tools.
- 2+ years of experience with Azure Data Factory and Snowflake.
- Medicaid Domain Knowledge is a plus.
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Entry Level Enterprise Engineer Jobs: Frequently Asked Questions
How do I get an entry level enterprise engineer job?
Focus on building hands-on experience through internships, capstone projects, or open-source contributions that demonstrate you can work at enterprise scale. Employers at this level look for familiarity with enterprise tools and platforms, strong troubleshooting instincts, and the ability to collaborate across teams. A well-documented portfolio project that solves a real infrastructure or systems problem can set you apart from other new graduates.
Which companies hire entry level enterprise engineers?
Companies hiring entry level enterprise engineers right now include Meter, Esri, and FanDuel, based on current listings on Migrate Mate as of November 2026. At this level, you'll find openings across large technology companies, managed service providers, and enterprise software vendors that run structured new-grad programs alongside direct-hire roles.
Are there remote entry level enterprise engineer jobs?
Yes, though most entry level enterprise engineer roles lean on-site for mentorship and onboarding reasons. About 27% of entry level enterprise engineer openings are remote or hybrid as of November 2026, so candidates flexible on location will have the widest range of options at this stage of their career.
Are these new grad enterprise engineer jobs?
Yes, the listings here include new grad, recent graduate, and junior enterprise engineer roles. A posting is new-grad friendly when it welcomes zero to two years of experience, accepts internship or co-op work in place of full-time history, or calls out a degree in lieu of prior employment. If the job description lists a portfolio or relevant coursework as acceptable, it's a solid new-grad target.
Which industries hire the most entry level enterprise engineers?
Entry Level enterprise engineer roles concentrate in Technology & Software, Energy, and Artificial Intelligence, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they run large, complex internal systems that need engineers who can learn quickly, follow established processes, and grow into more specialized responsibilities over time.