Entry Level Enterprise Support Engineer Jobs
New grad enterprise support engineer jobs attract recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship background can carry more weight than a long resume. Most openings mix on-site, remote, and hybrid settings across Technology & Software, Consulting & Professional Services, and Manufacturing, with employers like Molex, Boston Consulting, and Harness 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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Find JobsEntry Level Enterprise Support Engineer Job Market
Who's Hiring
- Molex18
- Boston Consulting18
- Harness16
- Abacus.Ai7
- Paylocity6
Top Industries Hiring
- Technology & Software82
- Consulting & Professional Services24
- Manufacturing14
- Electronics & Hardware13
- Accounting & Auditing7
Entry Level Enterprise Support Engineer Jobs: Frequently Asked Questions
How do I get an entry level enterprise support engineer job?
Start by building hands-on experience through internships, lab projects, or help-desk roles, since entry level enterprise support engineer positions typically look for candidates who can demonstrate troubleshooting ability and familiarity with enterprise tools over a long work history. Certifications in networking, cloud platforms, or ITSM frameworks like CompTIA A+, CCNA, or ITIL give new candidates a concrete edge during screening.
Which companies hire entry level enterprise support engineers?
Companies hiring entry level enterprise support engineers right now include Molex, Boston Consulting, and Harness, based on current listings on Migrate Mate as of November 2026. At this level, hiring comes from a wide range of organizations, including managed service providers, large technology firms, and enterprise software companies that maintain dedicated support teams.
Are there remote entry level enterprise support engineer jobs?
Yes, though on-site and hybrid roles are still common at the entry level. About 44% of entry level enterprise support engineer openings are remote or hybrid as of November 2026, so candidates who prefer flexibility have real options while those who want in-person mentorship can find that too.
Are these new grad enterprise support engineer jobs?
Yes, many of these listings are new grad and junior roles that welcome recent graduates and candidates with little to no professional experience. A new grad friendly posting typically calls for zero to two years of experience, accepts internships or academic projects as qualifications, and treats a strong portfolio or relevant coursework as equivalent to full-time work history.
Which industries hire the most entry level enterprise support engineers?
Entry Level enterprise support engineer roles concentrate in Technology & Software, Consulting & Professional Services, and Manufacturing, based on current listings on Migrate Mate as of November 2026. These sectors rely heavily on complex internal systems and large user bases, which creates steady demand for entry level support talent to handle escalations, deployments, and day-to-day technical issues.