Entry Level Lead Data Architect Jobs
New grad lead data architect jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship project can matter more than a long resume. Most openings are on-site and hybrid roles across Technology & Software, Consulting & Professional Services, and Insurance, with employers like Synertex, Grid Dynamics, and Tiger Analytics hiring at this level now.
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Showing 5 of 17+ Entry Level Lead Data Architect jobs
INTRODUCTION
Hi Our client is looking for a GCP Data Architect project in Dallas, TX below is the detailed requirement.
ROLE AND RESPONSIBILITIES
Job positing Title: GCP Data Architect
Location: Dallas, TX
BASIC QUALIFICATIONS
- Bachelor’s degree in related field Big Data & Processing
- Hands on experience with PySpark for ETL/ELT, data transformation, and performance optimization
- Solid understanding of distributed data processing concepts Data & Cloud Architecture
- Strong experience designing data platforms on Google Cloud Platform (GCP)
- Experience with Data Lakes, data warehousing, and large scale migration programs
Data Lake Architecture & Storage
- Proven experience designing and implementing data lake architectures (e.g., Bronze/Silver/Gold or layered models)
- Strong knowledge of Cloud Storage (GCS) design, including bucket layout, naming conventions, lifecycle policies, and access controls
- Hands-on experience with columnar data formats (Parquet, Avro, ORC) and compression techniques
- Expertise in partitioning strategies, backfills, and large-scale data organization
Data Ingestion & Orchestration
- Experience building batch and streaming ingestion pipelines using GCP-native services
- Knowledge of Pub/Sub-based streaming architectures, event schema design, and versioning
- Strong understanding of incremental ingestion and CDC patterns, including idempotency and deduplication
- Hands-on experience with workflow orchestration tools (Cloud Composer / Airflow)
- Ability to design robust error handling, replay, and backfill mechanisms
Data Processing & Transformation
- Experience developing scalable batch and streaming pipelines using Dataflow (Apache Beam) and/or Spark (Dataproc)
- Strong proficiency in BigQuery SQL, including query optimization, partitioning, clustering, and cost control
- Hands-on experience with Hadoop MapReduce and ecosystem tools (Hive, Pig, Sqoop)
- Advanced Python programming skills for data engineering, including testing and maintainable code design
- Experience managing schema evolution while minimizing downstream impact
DevOps / CI CD
- Experience implementing CI/CD pipelines for data and analytics workloads
- Familiarity with Git based source control, build automation, and deployment strategies
Containers & Platform
- Experience with OpenShift Container Platform (OCP) for deploying data workloads and services
- Understanding of containerized architecture, scaling, and environment management
- Proven ability to build CI/CD pipelines for data and infrastructure workloads
- Experience managing secrets securely using GCP Secret Manager
- Ownership of observability, SLOs, dashboards, alerts, and runbooks
- Proficiency in logging, monitoring, and alerting for data pipelines and platform reliability
Data Governance, Quality & Metadata
- Experience implementing data catalogs, metadata management, and ownership models
- Understanding of data lineage for auditability and troubleshooting
- Strong focus on data quality frameworks, including validation, freshness checks, and alerting
- Experience defining and enforcing data contracts, schemas, and SLAs
PREFERRED QUALIFICATIONS
- Hands-on experience implementing fine-grained access controls for BigQuery and GCS
- Experience with Sprint planning and helping team technically
- Strong stakeholder communication and solution architecture skills
INTRODUCTION
Hi Our client is looking for a GCP Data Architect project in Dallas, TX below is the detailed requirement.
ROLE AND RESPONSIBILITIES
Job positing Title: GCP Data Architect
Location: Dallas, TX
BASIC QUALIFICATIONS
- Bachelor’s degree in related field Big Data & Processing
- Hands on experience with PySpark for ETL/ELT, data transformation, and performance optimization
- Solid understanding of distributed data processing concepts Data & Cloud Architecture
- Strong experience designing data platforms on Google Cloud Platform (GCP)
- Experience with Data Lakes, data warehousing, and large scale migration programs
Data Lake Architecture & Storage
- Proven experience designing and implementing data lake architectures (e.g., Bronze/Silver/Gold or layered models)
- Strong knowledge of Cloud Storage (GCS) design, including bucket layout, naming conventions, lifecycle policies, and access controls
- Hands-on experience with columnar data formats (Parquet, Avro, ORC) and compression techniques
- Expertise in partitioning strategies, backfills, and large-scale data organization
Data Ingestion & Orchestration
- Experience building batch and streaming ingestion pipelines using GCP-native services
- Knowledge of Pub/Sub-based streaming architectures, event schema design, and versioning
- Strong understanding of incremental ingestion and CDC patterns, including idempotency and deduplication
- Hands-on experience with workflow orchestration tools (Cloud Composer / Airflow)
- Ability to design robust error handling, replay, and backfill mechanisms
Data Processing & Transformation
- Experience developing scalable batch and streaming pipelines using Dataflow (Apache Beam) and/or Spark (Dataproc)
- Strong proficiency in BigQuery SQL, including query optimization, partitioning, clustering, and cost control
- Hands-on experience with Hadoop MapReduce and ecosystem tools (Hive, Pig, Sqoop)
- Advanced Python programming skills for data engineering, including testing and maintainable code design
- Experience managing schema evolution while minimizing downstream impact
DevOps / CI CD
- Experience implementing CI/CD pipelines for data and analytics workloads
- Familiarity with Git based source control, build automation, and deployment strategies
Containers & Platform
- Experience with OpenShift Container Platform (OCP) for deploying data workloads and services
- Understanding of containerized architecture, scaling, and environment management
- Proven ability to build CI/CD pipelines for data and infrastructure workloads
- Experience managing secrets securely using GCP Secret Manager
- Ownership of observability, SLOs, dashboards, alerts, and runbooks
- Proficiency in logging, monitoring, and alerting for data pipelines and platform reliability
Data Governance, Quality & Metadata
- Experience implementing data catalogs, metadata management, and ownership models
- Understanding of data lineage for auditability and troubleshooting
- Strong focus on data quality frameworks, including validation, freshness checks, and alerting
- Experience defining and enforcing data contracts, schemas, and SLAs
PREFERRED QUALIFICATIONS
- Hands-on experience implementing fine-grained access controls for BigQuery and GCS
- Experience with Sprint planning and helping team technically
- Strong stakeholder communication and solution architecture skills
See All 17 Entry Level Lead Data Architect Jobs
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Find JobsEntry Level Lead Data Architect Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Consulting & Professional Services
- Insurance
Entry Level Lead Data Architect Jobs: Frequently Asked Questions
How do I get an entry level lead data architect job?
Build a portfolio that shows you can design and document a data model from scratch, even if the project is personal or academic. Employers at this level look for familiarity with SQL, cloud data platforms, and schema design principles. Internship experience, capstone projects, or open-source contributions all signal readiness. Certifications in platforms like Snowflake, dbt, or AWS help close gaps a short resume can't cover.
Which companies hire entry level lead data architects?
Companies hiring entry level lead data architects right now include Synertex, Grid Dynamics, and Tiger Analytics, based on current listings on Migrate Mate as of November 2026. At this level, hiring tends to come from technology companies, financial services firms, and healthcare organizations that are scaling their data infrastructure and willing to develop candidates who show strong fundamentals.
Are there remote entry level lead data architect jobs?
Yes, though on-site and hybrid roles remain common at this stage. About 64% of entry level lead data architect openings are remote or hybrid as of November 2026, so options exist across work settings. Candidates open to on-site positions typically see a wider pool of roles, since some employers prefer in-person onboarding for junior architecture hires.
Are these new grad lead data architect jobs?
Yes, these listings include new grad, recent graduate, and junior roles that explicitly welcome candidates with zero to two years of experience. A new grad friendly posting typically invites internship experience or a portfolio in place of full-time work history, and does not require prior team leadership. Look for language like 'entry level,' 'junior,' or 'associate' in the job title or requirements section.
Which industries hire the most entry level lead data architects?
Entry Level lead data architect roles concentrate in Technology & Software, Consulting & Professional Services, and Insurance, based on current listings on Migrate Mate as of November 2026. These sectors tend to drive hiring at this level because they are actively building or modernizing data infrastructure and need early-career architects who can contribute to modeling, documentation, and governance work under senior direction.