Big Data Architect (Databricks & AWS Specialist)
Budget: $2 – $8 USD
Data Architect – Big Data & Cloud (Databricks, AWS, Redshift, Glue)
Contract Duration:
6 months to 1 year (Extendable)
Experience Required:
10+ Years Total | 2–3 Years as Data Architect
Location:
Remote
Shift Timing:
US Shift – 9 hours (confirmation required)
Skills Required:
Databricks
AWS (S3, Glue, Redshift, Lake Formation, EMR, Kinesis, RDS, DMS)
Apache Spark
Python, SQL, PySpark
Data Lake / Delta Lake
ETL Process, Data Warehousing
SAP Data Integration (BW, S/4HANA, BODS)
Job Description:
We are seeking a highly skilled and experienced Data Architect with deep expertise in Big Data technologies, Data bricks solutions, and SAP integration—preferably within the manufacturing industry. This role demands a strong mix of technical leadership, hands-on architecture, and cost-efficient cloud infrastructure design.
Key Responsibilities:
Design and implement scalable, secure, and high-performance Big Data architectures using Databricks, Apache Spark, and cloud-native services.
Lead the full data architecture lifecycle: requirements gathering, design, deployment, and optimization.
Develop reusable and repeatable data ingestion pipelines for integrating ERP and business systems (SAP, Salesforce, HR, Factory, Marketing, etc.).
Collaborate across teams to bring SAP data into modern platforms.
Drive cloud cost optimization strategies to ensure efficient resource usage.
Provide technical leadership and mentorship to engineering teams.
Establish and enforce standards for data governance, quality, and security.
Translate business needs into technical solutions and robust data models.
Stay updated with the latest trends in data architecture and analytics.
Required Qualifications:
6+ years in Big Data architecture and engineering (Databricks & AWS tech stack).
3+ years of experience with AWS services: S3, Glue, Redshift, Lake Formation, EMR, Kinesis, RDS, DMS.
Strong hands-on experience with Databricks, Apache Spark, Delta Lake, and MLflow.
Proficiency in Python, SQL, and PySpark.
Experience extracting and integrating data from SAP (BW, S/4HANA, BODS).
Solid understanding of data modeling, data lakehouse architecture, and ETL/ELT processes.
Proven ability to lead data engineering teams and manage projects.
Bachelor's degree in Computer Science, IT, Data Science, or related field.
Excellent communication and stakeholder management skills.
Preferred Qualifications:
Experience in the manufacturing domain (production, supply chain, quality systems).
Certifications in Databricks, AWS, or data architecture.
Familiarity with CI/CD pipelines, DevOps practices, and Infrastructure as Code (e.g., Terraform)
: Softgoway
Contract Duration:
6 months to 1 year (Extendable)
Experience Required:
10+ Years Total | 2–3 Years as Data Architect
Location:
Remote
Shift Timing:
US Shift – 9 hours (confirmation required)
Skills Required:
Databricks
AWS (S3, Glue, Redshift, Lake Formation, EMR, Kinesis, RDS, DMS)
Apache Spark
Python, SQL, PySpark
Data Lake / Delta Lake
ETL Process, Data Warehousing
SAP Data Integration (BW, S/4HANA, BODS)
Job Description:
We are seeking a highly skilled and experienced Data Architect with deep expertise in Big Data technologies, Data bricks solutions, and SAP integration—preferably within the manufacturing industry. This role demands a strong mix of technical leadership, hands-on architecture, and cost-efficient cloud infrastructure design.
Key Responsibilities:
Design and implement scalable, secure, and high-performance Big Data architectures using Databricks, Apache Spark, and cloud-native services.
Lead the full data architecture lifecycle: requirements gathering, design, deployment, and optimization.
Develop reusable and repeatable data ingestion pipelines for integrating ERP and business systems (SAP, Salesforce, HR, Factory, Marketing, etc.).
Collaborate across teams to bring SAP data into modern platforms.
Drive cloud cost optimization strategies to ensure efficient resource usage.
Provide technical leadership and mentorship to engineering teams.
Establish and enforce standards for data governance, quality, and security.
Translate business needs into technical solutions and robust data models.
Stay updated with the latest trends in data architecture and analytics.
Required Qualifications:
6+ years in Big Data architecture and engineering (Databricks & AWS tech stack).
3+ years of experience with AWS services: S3, Glue, Redshift, Lake Formation, EMR, Kinesis, RDS, DMS.
Strong hands-on experience with Databricks, Apache Spark, Delta Lake, and MLflow.
Proficiency in Python, SQL, and PySpark.
Experience extracting and integrating data from SAP (BW, S/4HANA, BODS).
Solid understanding of data modeling, data lakehouse architecture, and ETL/ELT processes.
Proven ability to lead data engineering teams and manage projects.
Bachelor's degree in Computer Science, IT, Data Science, or related field.
Excellent communication and stakeholder management skills.
Preferred Qualifications:
Experience in the manufacturing domain (production, supply chain, quality systems).
Certifications in Databricks, AWS, or data architecture.
Familiarity with CI/CD pipelines, DevOps practices, and Infrastructure as Code (e.g., Terraform)
: Softgoway
Related categories:
Python
Linux
Amazon Web Services
Hadoop
Data Warehousing
Data Architecture
Big Data
Apache Spark