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HomeCompaniesBridgeheaditData Integration Engineer

Data Integration Engineer

Bridgeheadit · San Antonio, Texas, 78232, United States · Active · BambooHR

Job facts

FieldValue
CompanyBridgeheadit
TitleData Integration Engineer
Normalized title-
Department / teamSystems Development
LocationSan Antonio, United States
Work model-
Employment typeFull Time
Salary-
Statusactive
ATS providerBambooHR
Posted / first seen2025-10-09 / 2026-05-30
Changed / last seen2026-05-30 / 2026-06-06

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PageWhat it containsOpen
Company jobsActive postings from Bridgeheadit.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through BambooHR.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in San Antonio.Open
Department jobsActive postings in Systems Development.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyBridgeheadit
Source43472306-817a-40c6-9412-ea3f0cfc6fdc
ATS providerBambooHR

Description

Position Summary : The Data Integration Engineer will own the design, build, and operation of scalable data pipelines and warehouse models that power analytics and operational reporting. You’ll integrate diverse sources (databases, APIs, SaaS apps, flat files), and engineer performant ELT/ETL in the cloud. You’ll collaborate closely with analytics, app dev, and business stakeholders to turn requirements into trusted, production-grade datasets. Duties/Responsibilities: Data Pipeline Development Design and implement scalable ETL/ELT pipelines (batch and near-real-time) to ingest from databases, APIs, SaaS, and flat files into Snowflake, Azure Synapse, or similar. Build integrations using tools such as Azure Data Factory (ADF), Fivetran, CData Sync, and Boomi; extend with custom code where needed. Write clean, maintainable code (primarily SQL, plus Python or PHP when required for custom connectors, transformations, or microservices). Optimize workflows for performance, reliability, and scalability (partitioning, parallelism, incremental loads, CDC, idempotency, retry/rollback). Manage Datawarehouse platforms such as Azure Synapse and Snowflake Troubleshoot data pipeline failures and errors. Data Warehouse Management Develop and maintain data models, schemas, views, and stored procedures; manage staging/core/mart layers and source to target mappings. Implement data quality validation and monitoring (null/dup/range checks, schema drift detection, reconciliation). Respond to and troubleshoot errors identified. Apply warehouse best practices (clustering/partitioning, cost governance, role-based access, tagging/lineage). SQL & Python Support Complete complex SQL queries, refactors (window functions, CTE chains), and performance tuning (explain plans, pruning, join strategy). Create and/or troubleshoot Python notebooks (packaging, scheduling, secret mgmt) and integration into pipelines.  Collaboration & Documentation Partner with data analysts and stakeholders to clarify requirements and acceptance criteria and translate into source to target and technical designs. Maintain technical specs, data flow diagrams, and operational procedures; contribute to standards and reusable patterns. Qualifications: The ideal candidate will possess the following abilities, attributes, experience and skills: 4+ years’ experience in Data Warehousing and Data Engineering. Strong experience with Data Warehouse as a Service (DWaaS) platforms (Snowflake, BigQuery, etc). Strong SQL skills and ability to write queries and data extracts. Experience working with different database types Experience working with and troubleshooting different ETL tools such as Azure Data Factory, Boomi, Fivetran, and CData Sync. Strong understanding of DWaaS database architecture and ability to design and build optimal data processing pipelines. Demonstrated skill in designing highly scalable ETL processes with complex data transformations, data formats including data cleansing, data quality assessment, error handling and monitoring. Design, develop, manage, and monitor complex ETL data pipelines and support it through all environment runways. Experience with Python/JavaScript or other scripting languages is a plus. Provide Support and troubleshooting for data platforms. Manage and prioritize multiple assignments. Ability to work individually and as a team. Provide technical guidance and mentoring for other team members. Good communication and cross functional skills. Bridgehead IT is proud to be an equal opportunity workplace and is an affirmative action employer.

Full job record

Job IDbcf6bec7cc3c9e29f1819fd97a71685b5f848a60
Org IDf8a26161-29e7-40a4-8340-8ee821f000fd
Source ID43472306-817a-40c6-9412-ea3f0cfc6fdc
Board ID43472306-817a-40c6-9412-ea3f0cfc6fdc
Providerbamboohr
Provider Job Key194
TitleData Integration Engineer
Normalized Title
Statusactive
Activeyes
Location TextSan Antonio, Texas, 78232, United States
DepartmentSystems Development
Team
Employment Typefull_time
Workplace Type
Remote Policy
CountryUnited States
Region
CitySan Antonio
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://bridgeheadit.bamboohr.com/careers/194
Apply URLhttps://bridgeheadit.bamboohr.com/careers/194
First Seen At2026-05-30 05:47:59Z
Last Seen At2026-06-06 10:28:09Z
Last Checked At2026-06-06 10:28:09Z
Last Changed At2026-05-30 05:47:59Z
Inactive At
Source Posted At2025-10-09 00:00:00Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=bamboohr/board=bridgeheadit/date=2026-06-06/2026-06-06T10-28-08-913Z-06707e8173d42409ee909e447c22addc34d8e3a429bedaa84253e74c402d9ea2.json
Event Fields
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Parsed Structured
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Extensions
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    "description": "<p><span><span style=\"font-weight: bold\">Position Summary</span></span><span>:</span></p>\n<p>The Data Integration Engineer will own the design, build, and operation of scalable data pipelines and warehouse models that power analytics and operational reporting. You’ll integrate diverse sources (databases, APIs, SaaS apps, flat files), and engineer performant ELT/ETL in the cloud. You’ll collaborate closely with analytics, app dev, and business stakeholders to turn requirements into trusted, production-grade datasets.</p>\n<p><br><br></p>\n<p><span style=\"font-weight: bold\">Duties/Responsibilities: </span></p>\n<p>Data Pipeline Development</p>\n<ul>\n<li>Design and implement scalable ETL/ELT pipelines (batch and near-real-time) to ingest from databases, APIs, SaaS, and flat files into Snowflake, Azure Synapse, or similar.</li>\n<li>Build integrations using tools such as Azure Data Factory (ADF), Fivetran, CData Sync, and Boomi; extend with custom code where needed.</li>\n<li>Write clean, maintainable code (primarily SQL, plus Python or PHP when required for custom connectors, transformations, or microservices).</li>\n<li>Optimize workflows for performance, reliability, and scalability (partitioning, parallelism, incremental loads, CDC, idempotency, retry/rollback).</li>\n<li>Manage Datawarehouse platforms such as Azure Synapse and Snowflake</li>\n<li>Troubleshoot data pipeline failures and errors.</li>\n</ul>\n<p>Data Warehouse Management</p>\n<ul>\n<li>Develop and maintain data models, schemas, views, and stored procedures; manage staging/core/mart layers and source to target mappings.</li>\n<li>Implement data quality validation and monitoring (null/dup/range checks, schema drift detection, reconciliation).</li>\n<li>Respond to and troubleshoot errors identified.</li>\n<li>Apply warehouse best practices (clustering/partitioning, cost governance, role-based access, tagging/lineage).</li>\n</ul>\n<p>SQL &amp; Python Support</p>\n<ul>\n<li>Complete complex SQL queries, refactors (window functions, CTE chains), and performance tuning (explain plans, pruning, join strategy).</li>\n<li>Create and/or troubleshoot Python notebooks (packaging, scheduling, secret mgmt) and integration into pipelines.</li>\n</ul>\n<p> Collaboration &amp; Documentation</p>\n<ul>\n<li>Partner with data analysts and stakeholders to clarify requirements and acceptance criteria and translate into source to target and technical designs.</li>\n<li>Maintain technical specs, data flow diagrams, and operational procedures; contribute to standards and reusable patterns.</li>\n</ul>\n<p> </p>\n<p><span style=\"font-weight: bold\">Qualifications: </span></p>\n<p>The ideal candidate will possess the following abilities, attributes, experience and skills:</p>\n<ul>\n<li>4+ years’ experience in Data Warehousing and Data Engineering.</li>\n<li>Strong experience with Data Warehouse as a Service (DWaaS) platforms (Snowflake, BigQuery, etc).</li>\n<li>Strong SQL skills and ability to write queries and data extracts.</li>\n<li>Experience working with different database types</li>\n<li>Experience working with and troubleshooting different ETL tools such as Azure Data Factory, Boomi, Fivetran, and CData Sync.</li>\n<li>Strong understanding of DWaaS database architecture and ability to design and build optimal data processing pipelines.</li>\n<li>Demonstrated skill in designing highly scalable ETL processes with complex data transformations, data formats including data cleansing, data quality assessment, error handling and monitoring.</li>\n<li>Design, develop, manage, and monitor complex ETL data pipelines and support it through all environment runways.</li>\n<li>Experience with Python/JavaScript or other scripting languages is a plus.</li>\n<li>Provide Support and troubleshooting for data platforms.</li>\n<li>Manage and prioritize multiple assignments.</li>\n<li>Ability to work individually and as a team.</li>\n<li>Provide technical guidance and mentoring for other team members.</li>\n<li>Good communication and cross functional skills.</li>\n</ul>\n<p> </p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">Bridgehead IT is proud to be an equal opportunity workplace and is an affirmative action employer.</span></p>",
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