15 Apache Atlas Jobs

Create Solution Outline and Macro Design to describe end to end product implementation in Data Platforms including, System integration, Data ingestion, Data processing, Serving layer, Design Patterns, Platform Architecture Principles for Data platform Contribute to pre-sales, sales support through RfP responses, Solution Architecture, Planning and Estimation Contribute to reusable components / asset / accelerator development to support capability development Participate in Customer presentations as Platform Architects / Subject Matter Experts on Big Data, Azure Cloud and related technologies Participate in customer PoCs to deliver the outcomes Participate in delivery reviews / product reviews, quality assurance and work as design authority Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience in designing of data products providing descriptive, prescriptive, and predictive analytics to end users or other systems Experience in data engineering and architecting data platforms Experience in architecting and implementing Data Platforms Azure Cloud Platform Experience on Azure cloud is mandatory (ADLS Gen 1 / Gen2, Data Factory, Databricks, Synapse Analytics, Azure SQL, Cosmos DB, Event hub, Snowflake), Azure Purview, Microsoft Fabric, Kubernetes, Terraform, Airflow Experience in Big Data stack (Hadoop ecosystem Hive, HBase, Kafka, Spark, Scala PySpark, Python etc.) with Cloudera or Hortonworks Preferred technical and professional experience Experience in architecting complex data platforms on Azure Cloud Platform and On-Prem Experience and exposure to implementation of Data Fabric and Data Mesh concepts and solutions like Microsoft Fabric or Starburst or Denodo or IBM Data Virtualisation or Talend or Tibco Data Fabric Exposure to Data Cataloging and Governance solutions like Collibra, Alation, Watson Knowledge Catalog, dataBricks unity Catalog, Apache Atlas, Snowflake Data Glossary etc

Create Solution Outline and Macro Design to describe end to end product implementation in Data Platforms including, System integration, Data ingestion, Data processing, Serving layer, Design Patterns, Platform Architecture Principles for Data platform Contribute to pre-sales, sales support through RfP responses, Solution Architecture, Planning and Estimation Contribute to reusable components / asset / accelerator development to support capability development Participate in Customer presentations as Platform Architects / Subject Matter Experts on Big Data, Azure Cloud and related technologies Participate in customer PoCs to deliver the outcomes Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Candidates must have experience in designing of data products providing descriptive, prescriptive, and predictive analytics to end users or other systems 10 - 15 years of experience in data engineering and architecting data platforms 5 – 8 years’ experience in architecting and implementing Data Platforms Azure Cloud Platform. 5 – 8 years’ experience in architecting and implementing Data Platforms on-prem (Hadoop or DW appliance) Experience on Azure cloud is mandatory (ADLS Gen 1 / Gen2, Data Factory, Databricks, Synapse Analytics, Azure SQL, Cosmos DB, Event hub, Snowflake), Azure Purview, Microsoft Fabric, Kubernetes, Terraform, Airflow. Experience in Big Data stack (Hadoop ecosystem Hive, HBase, Kafka, Spark, Scala PySpark, Python etc.) with Cloudera or Hortonworks Preferred technical and professional experience Exposure to Data Cataloging and Governance solutions like Collibra, Alation, Watson Knowledge Catalog, dataBricks unity Catalog, Apache Atlas, Snowflake Data Glossary etc Candidates should have experience in delivering both business decision support systems (reporting, analytics) and data science domains / use cases

Dear Candidate, We are looking for a Big Data Developer to build and maintain scalable data processing systems. The ideal candidate will have experience handling large datasets and working with distributed computing frameworks. Key Responsibilities: Design and develop data pipelines using Hadoop, Spark, or Flink. Optimize big data applications for performance and reliability. Integrate various structured and unstructured data sources. Work with data scientists and analysts to prepare datasets. Ensure data quality, security, and lineage across platforms. Required Skills & Qualifications: Experience with Hadoop ecosystem (HDFS, Hive, Pig) and Apache Spark. Proficiency in Java, Scala, or Python. Familiarity with data ingestion tools (Kafka, Sqoop, NiFi). Strong understanding of distributed computing principles. Knowledge of cloud-based big data services (e.g., EMR, Dataproc, HDInsight). Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

Create Solution Outline and Macro Design to describe end to end product implementation in Data Platforms including, System integration, Data ingestion, Data processing, Serving layer, Design Patterns, Platform Architecture Principles for Data platform Contribute to pre-sales, sales support through RfP responses, Solution Architecture, Planning and Estimation Contribute to reusable components / asset / accelerator development to support capability development Participate in Customer presentations as Platform Architects / Subject Matter Experts on Big Data, Azure Cloud and related technologies Participate in customer PoCs to deliver the outcomes Participate in delivery reviews / product reviews, quality assurance and work as design authority Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience in designing of data products providing descriptive, prescriptive, and predictive analytics to end users or other systems Experience in data engineering and architecting data platforms Experience in architecting and implementing Data Platforms Azure Cloud Platform Experience on Azure cloud is mandatory (ADLS Gen 1 / Gen2, Data Factory, Databricks, Synapse Analytics, Azure SQL, Cosmos DB, Event hub, Snowflake), Azure Purview, Microsoft Fabric, Kubernetes, Terraform, Airflow Experience in Big Data stack (Hadoop ecosystem Hive, HBase, Kafka, Spark, Scala PySpark, Python etc.) with Cloudera or Hortonworks Preferred technical and professional experience Experience in architecting complex data platforms on Azure Cloud Platform and On-Prem Experience and exposure to implementation of Data Fabric and Data Mesh concepts and solutions like Microsoft Fabric or Starburst or Denodo or IBM Data Virtualisation or Talend or Tibco Data Fabric Exposure to Data Cataloging and Governance solutions like Collibra, Alation, Watson Knowledge Catalog, dataBricks unity Catalog, Apache Atlas, Snowflake Data Glossary etc

Role Overview: Lead the architectural design and implementation of a secure, scalable Cloudera-based Data Lakehouse for one of India’s top public sector banks. Key Responsibilities: * Design end-to-end Lakehouse architecture on Cloudera * Define data ingestion, processing, storage, and consumption layers * Guide data modeling, governance, lineage, and security best practices * Define migration roadmap from existing DWH to CDP * Lead reviews with client stakeholders and engineering teams Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Proven experience with Cloudera CDP, Spark, Hive, HDFS, Iceberg * Deep understanding of Lakehouse patterns and data mesh principles * Familiarity with data governance tools (e.g., Apache Atlas, Collibra) * Banking/FSI domain knowledge highly desirable.

Join Us in Transforming Healthcare with the Power of Data & AI At Innovaccer, were on a advanced Healthcare Intelligence Platform ever created. Grounded in an AI-first design philosophy, our platform turns complex health data into real-time intelligence, empowering healthcare systems to make faster, smarter decisions. We are building a unified , end-to-end data platform that spans Data Acquisition & Integration, Master Data Management , Data Classification & Governance , Advanced Analytics & AI Studio , App Marketplace , AI-as-BI capabilities, etc. All of this is powered by an Agent-first approach , enabling customers to build solutions dynamically and at scale. Youll have the opportunity to define and develop platform capabilities that help healthcare organizations tackle some of the industrys most pressing challenges, such as Kidney disease management, Clinical trials optimization for pharmaceutical companies, Supply chain intelligence for pharmacies, and many more real-world applications. Were looking for talented engineers and platform thinkers who thrive on solving large-scale, complex, and meaningful problems. If youre excited about working at the intersection of healthcare, AI, and cutting-edge platform engineering, wed love to hear from you. About the Role We are looking for a Staff Engineer to design and develop highly scalable, low-latency data platforms and processing engines. This role is ideal for engineers who enjoy building core systems and infrastructure that enable mission-critical analytics at scale. Youll work on solving some of the toughest data engineering challenges in healthcare. A Day in the Life Architect, design, and build scalable data tools and frameworks. Collaborate with cross-functional teams to ensure data compliance, security, and usability. Lead initiatives around metadata management, data lineage, and data cataloging. Define and evangelize standards and best practices across data engineering teams. Own the end-to-end lifecycle of tooling from prototyping to production deployment. Mentor and guide junior engineers and contribute to technical leadership across the organization. Drive innovation in privacy-by-design, regulatory compliance (e.g., HIPAA), and data observability solutions. What You Need 8+ years of experience in software engineering with strong experience building distributed systems. Proficient in backend development (Python, Java, or Scala or Go) and familiar with RESTful API design. Expertise in modern data stacks: Kafka, Spark, Airflow, Snowflake etc. Experience with open-source data governance frameworks like Apache Atlas, Amundsen, or DataHub is a big plus. Familiarity with cloud platforms (AWS, Azure, GCP) and their native data governance offerings. Bachelor's or Masters degree in Computer Science, Engineering, or a related field.

About the Role We are looking for a Staff Engineer to lead the design and development of a scalable, secure, and robust data platform. You will play a key role in building data platform capabilities for data quality, metadata management, lineage tracking, and compliance across all data layers. If youre passionate about building foundational data infrastructure that accelerates innovation in healthcare, wed love to talk. A Day in the Life Architect, design, and build scalable data governance tools and frameworks. Collaborate with cross-functional teams to ensure data compliance, security, and usability. Lead initiatives around metadata management, data lineage, and data cataloging. Define and evangelize standards and best practices across data engineering teams. Own the end-to-end lifecycle of governance tooling from prototyping to production deployment. Mentor and guide junior engineers and contribute to technical leadership across the organization. Drive innovation in privacy-by-design, regulatory compliance (e.g., HIPAA), and data observability solutions. What You Need 8+ years of experience in software engineering. Strong experience building distributed systems for metadata management, data lineage, and quality tracking. Proficient in backend development (Python, Java, or Scala or Go) and familiar with RESTful API design. Expertise in modern data stacks: Kafka, Spark, Airflow, Snowflake etc. Experience with open-source data governance frameworks like Apache Atlas, Amundsen, or DataHub is a big plus. Familiarity with cloud platforms (AWS, Azure, GCP) and their native data governance offerings. Prior experience in building metadata management frameworks for scale. Bachelor's or Masters degree in Computer Science, Engineering, or a related field.

Create Solution Outline and Macro Design to describe end to end product implementation in Data Platforms including, System integration, Data ingestion, Data processing, Serving layer, Design Patterns, Platform Architecture Principles for Data platform Contribute to pre-sales, sales support through RfP responses, Solution Architecture, Planning and Estimation Contribute to reusable components / asset / accelerator development to support capability development Participate in Customer presentations as Platform Architects / Subject Matter Experts on Big Data, Azure Cloud and related technologies Participate in customer PoCs to deliver the outcomes Participate in delivery reviews / product reviews, quality assurance and work as design authority Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience in designing of data products providing descriptive, prescriptive, and predictive analytics to end users or other systems Experience in data engineering and architecting data platforms Experience in architecting and implementing Data Platforms Azure Cloud Platform Experience on Azure cloud is mandatory (ADLS Gen 1 / Gen2, Data Factory, Databricks, Synapse Analytics, Azure SQL, Cosmos DB, Event hub, Snowflake), Azure Purview, Microsoft Fabric, Kubernetes, Terraform, Airflow Experience in Big Data stack (Hadoop ecosystem Hive, HBase, Kafka, Spark, Scala PySpark, Python etc.) with Cloudera or Hortonworks Preferred technical and professional experience Experience in architecting complex data platforms on Azure Cloud Platform and On-Prem Experience and exposure to implementation of Data Fabric and Data Mesh concepts and solutions like Microsoft Fabric or Starburst or Denodo or IBM Data Virtualisation or Talend or Tibco Data Fabric Exposure to Data Cataloging and Governance solutions like Collibra, Alation, Watson Knowledge Catalog, dataBricks unity Catalog, Apache Atlas, Snowflake Data Glossary etc

Create Solution Outline and Macro Design to describe end to end product implementation in Data Platforms including, System integration, Data ingestion, Data processing, Serving layer, Design Patterns, Platform Architecture Principles for Data platform. Contribute to pre-sales, sales support through RfP responses, Solution Architecture, Planning and Estimation. Contribute to reusable components / asset / accelerator development to support capability development Participate in Customer presentations as Platform Architects / Subject Matter Experts on Big Data, Azure Cloud and related technologies Participate in customer PoCs to deliver the outcomes Participate in delivery reviews / product reviews, quality assurance and work as design authority Required education Bachelor's Degree Preferred education Non-Degree Program Required technical and professional expertise Experience in designing of data products providing descriptive, prescriptive, and predictive analytics to end users or other systems Experience in data engineering and architecting data platforms. Experience in architecting and implementing Data Platforms Azure Cloud Platform Experience on Azure cloud is mandatory (ADLS Gen 1 / Gen2, Data Factory, Databricks, Synapse Analytics, Azure SQL, Cosmos DB, Event hub, Snowflake), Azure Purview, Microsoft Fabric, Kubernetes, Terraform, Airflow Experience in Big Data stack (Hadoop ecosystem Hive, HBase, Kafka, Spark, Scala PySpark, Python etc.) with Cloudera or Hortonworks Preferred technical and professional experience Experience in architecting complex data platforms on Azure Cloud Platform and On-Prem Experience and exposure to implementation of Data Fabric and Data Mesh concepts and solutions like Microsoft Fabric or Starburst or Denodo or IBM Data Virtualisation or Talend or Tibco Data Fabric Exposure to Data Cataloging and Governance solutions like Collibra, Alation, Watson Knowledge Catalog, dataBricks unity Catalog, Apache Atlas, Snowflake Data Glossary etc

Create Solution Outline and Macro Design to describe end to end product implementation in Data Platforms including, System integration, Data ingestion, Data processing, Serving layer, Design Patterns, Platform Architecture Principles for Data platform Contribute to pre-sales, sales support through RfP responses, Solution Architecture, Planning and Estimation Contribute to reusable components / asset / accelerator development to support capability development Participate in Customer presentations as Platform Architects / Subject Matter Experts on Big Data, Azure Cloud and related technologies Participate in customer PoCs to deliver the outcomes Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Candidates must have experience in designing of data products providing descriptive, prescriptive, and predictive analytics to end users or other systems 10 - 15 years of experience in data engineering and architecting data platforms 5 – 8 years’ experience in architecting and implementing Data Platforms Azure Cloud Platform. 5 – 8 years’ experience in architecting and implementing Data Platforms on-prem (Hadoop or DW appliance) Experience on Azure cloud is mandatory (ADLS Gen 1 / Gen2, Data Factory, Databricks, Synapse Analytics, Azure SQL, Cosmos DB, Event hub, Snowflake), Azure Purview, Microsoft Fabric, Kubernetes, Terraform, Airflow. Experience in Big Data stack (Hadoop ecosystem Hive, HBase, Kafka, Spark, Scala PySpark, Python etc.) with Cloudera or Hortonworks Preferred technical and professional experience Exposure to Data Cataloging and Governance solutions like Collibra, Alation, Watson Knowledge Catalog, dataBricks unity Catalog, Apache Atlas, Snowflake Data Glossary etc Candidates should have experience in delivering both business decision support systems (reporting, analytics) and data science domains / use cases

LocationMumbai Experience15+ years in data engineering/architecture Role Overview: Lead the architectural design and implementation of a secure, scalable Cloudera-based Data Lakehouse for one of India’s top public sector banks. Key Responsibilities: * Design end-to-end Lakehouse architecture on Cloudera * Define data ingestion, processing, storage, and consumption layers * Guide data modeling, governance, lineage, and security best practices * Define migration roadmap from existing DWH to CDP * Lead reviews with client stakeholders and engineering teams Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Skills Required: * Proven experience with Cloudera CDP, Spark, Hive, HDFS, Iceberg * Deep understanding of Lakehouse patterns and data mesh principles * Familiarity with data governance tools (e.g., Apache Atlas, Collibra) * Banking/FSI domain knowledge highly desirable

Role Overview : We are hiring aTalend Data Quality Developerto design and implement robust data quality (DQ) frameworks in a Cloudera-based data lakehouse environment. The role focuses on building rule-driven validation and monitoring processes for migrated data pipelines, ensuring high levels of data trust and regulatory compliance across critical banking domains. Key Responsibilities : Design and implement data quality rules using Talend DQ Studio , tailored to validate customer, account, transaction, and KYC datasets within the Cloudera Lakehouse. Create reusable templates for profiling, validation, standardization, and exception handling. Integrate DQ checks within PySpark-based ingestion and transformation pipelines targeting Apache Iceberg tables . Ensure compatibility with Cloudera components (HDFS, Hive, Iceberg, Ranger, Atlas) and job orchestration frameworks (Airflow/Oozie). Perform initial and ongoing data profiling on source and target systems to detect data anomalies and drive rule definitions. Monitor and report DQ metrics through dashboards and exception reports. Work closely with data governance, architecture, and business teams to align DQ rules with enterprise definitions and regulatory requirements. Support lineage and metadata integration with tools like Apache Atlas or external catalogs. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience 5–10 years in data management, with 3+ years in Talend Data Quality tools. Platforms Experience in Cloudera Data Platform (CDP) , with understanding of Iceberg , Hive , HDFS , and Spark ecosystems. Languages/Tools Talend Studio (DQ module), SQL, Python (preferred), Bash scripting. Data Concepts Strong grasp of data quality dimensions—completeness, consistency, accuracy, timeliness, uniqueness. Banking Exposure Experience with financial services data (CIF, AML, KYC, product masters) is highly preferred.

Role Overview : We are looking for aTalend Data Catalog Specialistto drive enterprise data governance initiatives by implementingTalend Data Catalogand integrating it withApache Atlasfor unified metadata management within a Cloudera-based data lakehouse. The role involves establishing metadata lineage, glossary harmonization, and governance policies to enhance trust, discovery, and compliance across the data ecosystem Key Responsibilities: o Set up and configure Talend Data Catalog to ingest and manage metadata from source systems, data lake (HDFS), Iceberg tables, Hive metastore, and external data sources. o Develop and maintain business glossaries , data classifications, and metadata models. o Design and implement bi-directional integration between Talend Data Catalog and Apache Atlas to enable metadata synchronization , lineage capture, and policy alignment across the Cloudera stack. o Map technical metadata from Hive/Impala to business metadata defined in Talend. o Capture end-to-end lineage of data pipelines (e.g., from ingestion in PySpark to consumption in BI tools) using Talend and Atlas. o Provide impact analysis for schema changes, data transformations, and governance rule enforcement. o Support definition and rollout of enterprise data governance policies (e.g., ownership, stewardship, access control). o Enable role-based metadata access , tagging, and data sensitivity classification. o Work with data owners, stewards, and architects to ensure data assets are well-documented, governed, and discoverable. o Provide training to users on leveraging the catalog for search, understanding, and reuse. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 6–12 years in data governance or metadata management, with at least 2–3 years in Talend Data Catalog. Talend Data Catalog, Apache Atlas, Cloudera CDP, Hive/Impala, Spark, HDFS, SQL. Business glossary, metadata enrichment, lineage tracking, stewardship workflows. Hands-on experience in Talend–Atlas integration , either through REST APIs, Kafka hooks, or metadata bridges. Preferred technical and professional experience .

About the Role We are looking for a Staff Engineer to lead the design and development of a scalable, secure, and robust data platform. You will play a key role in building data platform capabilities for data quality, metadata management, lineage tracking, and compliance across all data layers. If youre passionate about building foundational data infrastructure that accelerates innovation in healthcare, wed love to talk. A Day in the Life Architect, design, and build scalable data governance tools and frameworks. Collaborate with cross-functional teams to ensure data compliance, security, and usability. Lead initiatives around metadata management, data lineage, and data cataloging. Define and evangelize standards and best practices across data engineering teams. Own the end-to-end lifecycle of governance tooling from prototyping to production deployment. Mentor and guide junior engineers and contribute to technical leadership across the organization. Drive innovation in privacy-by-design, regulatory compliance (e.g., HIPAA), and data observability solutions. What You Need 8+ years of experience in software engineering. Strong experience building distributed systems for metadata management, data lineage, and quality tracking. Proficient in backend development (Python, Java, or Scala or Go) and familiar with RESTful API design. Expertise in modern data stacks: Kafka, Spark, Airflow, Snowflake etc. Experience with open-source data governance frameworks like Apache Atlas, Amundsen, or DataHub is a big plus. Familiarity with cloud platforms (AWS, Azure, GCP) and their native data governance offerings. Prior experience in building metadata management frameworks for scale.

locationsIN - Bangaloreposted onPosted Today time left to applyEnd DateMay 22, 2025 (5 days left to apply) job requisition idR140300 Company Overview A.P. Moller - Maersk is an integrated container logistics company and member of the A.P. Moller Group. Connecting and simplifying trade to help our customers grow and thrive . With a dedicated team of over 95,000 employees, operating in 130 countries; we go all the way to enable global trade for a growing world . From the farm to your refrigerator, or the factory to your wardrobe, A.P. Moller - Maersk is developing solutions that meet customer needs from one end of the supply chain to the other. About the Team At Maersk, the Global Ocean Manifest team is at the heart of global trade compliance and automation. We build intelligent, high-scale systems that seamlessly integrate customs regulations across 100+ countries, ensuring smooth cross-border movement of cargo by ocean, rail, and other transport modes. Our mission is to digitally transform customs documentation, reducing friction, optimizing workflows, and automating compliance for a complex web of regulatory bodies, ports, and customs authorities. We deal with real-time data ingestion, document generation, regulatory rule engines, and multi-format data exchange while ensuring resilience and security at scale. Key Responsibilities Work with large, complex datasets and ensure efficient data processing and transformation. Collaborate with cross-functional teams to gather and understand data requirements. Ensure data quality, integrity, and security across all processes. Implement data validation, lineage, and governance strategies to ensure data accuracy and reliability. Build, optimize , and maintain ETL pipelines for structured and unstructured data , ensuring high throughput, low latency, and cost efficiency . Experience in building scalable, distributed data pipelines for processing real-time and historical data. Contribute to the architecture and design of data systems and solutions. Write and optimize SQL queries for data extraction, transformation, and loading (ETL). Advisory to Product Owners to identify and manage risks, debt, issues and opportunities for the technical improvement . Providing continuous improvement suggestions in internal code frameworks, best practices and guidelines . Contribute to engineering innovations that fuel Maersks vision and mission. Required Skills & Qualifications 4 + years of experience in data engineering or a related field. Strong problem-solving and analytical skills. E xperience on Java, Spring framework Experience in building data processing pipelines using Apache Flink and Spark. Experience in distributed data lake environments ( Dremio , Databricks, Google BigQuery , etc.) E xperience on Apache Kafka, Kafka Streams Experience working with databases. PostgreSQL preferred, with s olid experience in writin g and opti mizing SQL queries. Hands-on experience in cloud environments such as Azure Cloud (preferred), AWS, Google Cloud, etc. Experience with data warehousing and ETL processes . Experience in designing and integrating data APIs (REST/ GraphQL ) for real-time and batch processing. Knowledge on Great Expectations, Apache Atlas, or DataHub , would be a plus Knowledge on RBAC, encryption, GDPR compliance would be a plus Business skills Excellent communication and collaboration skills Ability to translate between technical language and business language, and communicate to different target groups Ability to understand complex design Possessing the ability to balance and find competing forces & opinions , within the development team Personal profile Fact based and result oriented Ability to work independently and guide the team Excellent verbal and written communication Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements. We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing . Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements. We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing .