Big Data Hadoop Architect Hybrid

DFBooking Careers; Seattle (WA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Paid time off

Parental leave

Learning budget

Home office allowance

Wellness program

Job summary

DFBooking Careers in Seattle is seeking a hands-on Big Data Hadoop Architect to lead the design and modernization of enterprise-scale data platforms. You will balance strategy with execution, drive cloud transformation, and build scalable, cost-efficient data ecosystems.

You will define architecture roadmaps, migrate to cloud-native stacks, and mentor engineering teams while collaborating with stakeholders to translate requirements into robust data solutions.

Qualifications

• 10–15+ years of IT experience with minimum 5+ years in Big Data Architecture.
• Strong expertise in Hadoop ecosystem and Spark-based data platforms.
• Hands-on cloud experience across AWS/Azure/GCP.
• Proficient in Java/Scala/Python and distributed system design.
• Experience with data warehousing, ETL frameworks, and data governance is a plus.

Responsibilities

• Define enterprise data architecture roadmap aligned with business goals.
• Architect and implement large-scale Hadoop/Spark-based data platforms.
• Lead migration from on-prem Hadoop clusters to cloud-native architectures.
• Design real-time and batch data pipelines using Kafka, Spark Streaming, Flink.
• Establish data lake/lakehouse architecture (Delta Lake, Iceberg, Hudi).
• Drive data modeling standards and ingestion frameworks.
• Collaborate with DevOps to implement CI/CD for data workflows.
• Provide technical leadership, code reviews, and mentoring to engineering teams.
• Collaborate with business stakeholders to translate requirements into technical solutions.

Skills

Hadoop Ecosystem

Apache Spark

Kafka / Pulsar / Flink

Java / Scala / Python

Distributed systems

Containerization

Data warehousing / ETL

Databricks / Snowflake

Tools

Databricks

Snowflake

Job description

We are hiring a Big Data Hadoop Architect to lead the design and modernization of enterprise-scale data platforms. This role requires a hands-on architect who can balance strategy with execution, drive cloud transformation, and build highly scalable, cost-efficient data ecosystems.

Key Responsibilities (Expanded & Realistic)

• Define enterprise data architecture roadmap aligned with business goals


• Architect and implement large-scale Hadoop/Spark-based data platforms


• Lead migration from on-prem Hadoop clusters to cloud-native architectures


• Design real-time and batch data pipelines using Kafka, Spark Streaming, Flink, etc.


• Establish data lake / lakehouse architecture (Delta Lake, Iceberg, Hudi)


• Drive data modeling standards (dimensional, data vault, normalized models)


• Build frameworks for data ingestion (ETL/ELT) from structured & unstructured sources


• Optimize cluster performance, cost, and resource utilization


• Define and enforce data governance, lineage, cataloging, and quality frameworks


• Implement security best practices (encryption, IAM, data masking, compliance – HIPAA/GDPR where applicable)


• Lead capacity planning and scalability strategies for petabyte-scale data


• Evaluate and introduce modern tools (Databricks, Snowflake, etc.) beyond Hadoop ecosystem


• Work closely with DevOps teams to implement CI/CD pipelines for data workflows


• Provide technical leadership, code reviews, and mentoring to engineering teams


• Collaborate with business stakeholders to translate requirements into technical solutions


• Drive incident resolution and root cause analysis for production data issues


• Ensure high availability and disaster recovery strategies are in place


• Influence tooling, vendor selection, and long-term data platform investments

Required Skills & Experience

10–15+ years of IT experience with minimum 5+ years in Big Data Architecture

Strong expertise in:

• Hadoop Ecosystem (HDFS, YARN, Hive, HBase)


• Apache Spark (Core, SQL, Streaming)


• Kafka / Pulsar / Flink

Hands-on experience with cloud platforms:

• AWS (EMR, S3, Glue, Redshift) OR


• Azure (Data Lake, Synapse, HDInsight) OR


• GCP (Dataproc, BigQuery)

• Strong programming skills in Java / Scala / Python


• Deep understanding of distributed systems, parallel processing, and data partitioning


• Experience with containerization (Docker, Kubernetes)


• Expertise in data warehousing and ETL frameworks

Preferred Qualifications

• Experience with Databricks, Snowflake, or modern lakehouse platforms


• Exposure to AI/ML pipelines and feature engineering systems


• Cloud certifications (AWS/Azure/GCP Architect level)


• Strong leadership and stakeholder management experience

Total Rewards & Benefits (Realistic US Package)

• Comprehensive Medical, Dental & Vision Insurance


• 401(k) with employer match (up to 5–6%)


• Paid Time Off (20–25 days) + Paid Holidays


• Parental Leave (12–16 weeks)


• Learning Budget ($2,500/year for certifications & courses)


• Home Office Setup Allowance ($1,000 one-time)


• Wellness Programs (Gym reimbursement, mental health support)