Big Data Technical Architect

Cloud Hybrid Technologies, LLC; Dallas (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading technology firm is seeking a highly experienced Technical Architect to join their team in Dallas, Texas. The ideal candidate will possess extensive knowledge of the Big Data ecosystem, particularly in Apache Spark, cloud data platforms like AWS, Azure, and Google Cloud. Candidates should have proven expertise in advanced SQL and Python, as well as strong leadership and mentoring skills. This role offers an opportunity to drive data quality and governance within a dynamic work environment.

Qualifications

• 15+ years of progressive experience in software engineering, at least 5 years in a technical role.
• Expert-level experience with Spark SQL, DataFrames/Datasets, and performance tuning.
• Experience in leading and mentoring technical teams.

Skills

Big Data ecosystem expertise

Apache Spark

Advanced SQL

Python for data engineering

Cloud Data Platforms (AWS, Azure, GCP)

Data quality engineering

Leadership and mentoring

SDLC understanding

Communication skills

Education

Bachelor's or master's degree in computer science, Engineering, or related quantitative field

Job description

• Bachelor's or master's degree in computer science, Engineering, or a related quantitative field.
• 15+ years of progressive experience in software engineering, with at least 5+ years in a Technical Architect, Lead Data Architect, or Principal Data Engineer role, specifically focused on data quality, data governance, or data platform architecture.
• Exceptional hands-on proficiency and deep architectural understanding of the Big Data ecosystem:
• Apache Spark (PySpark, Scala, or Java): Expert-level experience with Spark SQL, DataFrames/Datasets, streaming, and advanced performance tuning techniques.
• Distributed Storage & Processing: Hadoop, HDFS, S3, Delta Lake, Apache Iceberg, or similar data lake technologies.
• Streaming Technologies: Apache Kafka, AWS Kinesis, or similar high-throughput messaging systems.
• Cloud Data Platforms: Extensive experience designing and implementing solutions on AWS (e.g., EMR, Glue, Redshift, Lambda, Step Functions, S3), Azure (e.g., Databricks, Synapse Analytics, Data Lake Storage), or Google Cloud Platform (e.g., Dataproc, BigQuery, Cloud Storage).
• Expert-level hands-on experience with Advanced SQL for complex data analysis, validation, and optimization.
• Expert-level hands-on experience with Python for data engineering, automation, and developing robust data quality solutions.
• Proven track record of defining, designing, and implementing large-scale data automation frameworks.
• Demonstrated expertise in data quality engineering principles, methodologies, and tools (profiling, validation, cleansing, reconciliation, anomaly detection).
• Experience in leading and mentoring technical teams, fostering a culture of technical excellence and continuous improvement.
• Strong understanding of software development lifecycle (SDLC), DevOps practices, and integrating quality gates into CI/CD pipelines.
• Excellent communication, presentation, and interpersonal skills, with the ability to articulate complex technical concepts to diverse audiences, including senior leadership and non-technical stakeholders.

Cloud Hybrid is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. Cloud Hybrid will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will Cloud Hybrid require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract