Protiviti is hiring an AWS Data Engineering Manager to lead the design and delivery of scalable, secure, and reliable data platforms and pipelines on AWS. This hybrid role partners with clients across multiple industries to turn complex business and data requirements into practical AWS data solutions, with opportunities to guide architecture decisions, build trusted relationships, and strengthen Protiviti’s AWS data engineering capabilities.
What you can expect
- Hybrid workplace in Dallas, TX, with a client-dependent split between remote and in-person work
- Compensation: $125,000 to $200,000 base salary, depending on experience, skills, and geo (plus an annual bonus plan with a bonus target opportunity of 12%)
- Employee benefits: medical, dental, and vision coverages; FSA and HSA healthcare accounts; life and accident insurance; adoption and fertility assistance; paid parental leave up to 10 weeks; short- and long-term disability; and a 401(k) savings and investment plan with an employer match of 50% on the first 6% you contribute
- Time off and holidays: Choice Time Off (CTO) for vacation, personal needs, and sick time (up to 20 days per calendar year for new hires) and up to 11 paid holidays each calendar year
Responsibilities
- Lead the design and delivery of scalable, secure, and reliable data platforms and pipelines on AWS for clients across multiple industries
- Partner with clients to translate complex business and data requirements into practical AWS data solutions
- Lead significant data engineering workstreams by guiding delivery teams and remaining actively involved in architecture, design, and technical decision-making
- Develop trusted client relationships, mentor Consultants and Senior Consultants, and contribute to proposals that help expand Protiviti’s AWS data engineering capabilities
- Own architecture and delivery outcomes across multiple significant AWS data engineering engagements
- Convert ambiguous requirements into implementable data architectures, backlogs, and delivery plans
- Improve data engineering quality and consistency through reusable standards, patterns, and accelerators
- Develop team capability through coaching, technical reviews, and knowledge sharing
- Help create well-scoped follow-on work that addresses client data needs and produces measurable outcomes
Core requirements
- Strong experience designing and implementing enterprise data platforms and pipelines on AWS
- Hands-on expertise with core AWS data services including S3, Glue, Lambda, Step Functions, Athena, and Redshift
- Experience with large-scale or streaming technologies such as EMR, Spark or PySpark, Kinesis, or managed Kafka
- Advanced SQL plus strong data modeling, query optimization, and data warehouse or lakehouse concepts
- Proficiency in Python or a comparable data engineering programming language
- Experience ingesting data from diverse enterprise sources and formats, including databases, APIs, SaaS platforms, flat files, and unstructured content
- Data ingestion familiarity across formats such as parquet, Excel, CSV, EDI, email attachments, and PDF
- ETL pipeline design experience using AWS Glue, Lambda, or Step Functions
- Data modeling experience including building knowledge bases from extract-based inputs such as JDE extracts, contract records, and spend data
- Data quality profiling and validation, including a Phase 0 scorecard deliverable
- Familiarity with procurement data structures including PO lines, item master, vendor master, and contract terms (learning on the job acceptable, but comfort with messy enterprise data required)
- Ad-hoc analysis using S3, Athena, or DuckDB
- Ability to produce clean export files for enterprise integrations, including JDE import format and Oracle FBDI
- Experience implementing data quality, observability, reconciliation, metadata, cataloging, lineage, and governance controls
- Knowledge of AWS security concepts for data platforms, including IAM, encryption, network access, secrets management, and least-privilege design
- Experience with source control, CI/CD, automated testing, infrastructure as code, and production deployment practices for data solutions
- Experience leading complex technical engagements with multiple data sources, workstreams, or engineering teams
- Ability to estimate, plan, and structure data engineering engagements while managing technical risks and dependencies
- Strong client advisory, facilitation, executive communication, and stakeholder-management skills (consulting or systems integration experience is highly preferred)
- AWS Certified Solutions Architect – Associate (required)
- Preferred: AWS Certified Solutions Architect – Professional and AWS Certified Security – Specialty
- Education: Bachelor’s degree in a relevant discipline (e.g., MIS, IS, Comp Sci.)
- Experience: 5+ years working in professional services or industry
Technologies you’ll work with
- AWS, S3, Athena, DuckDB
- AWS Glue, AWS Lambda, Step Functions
- Redshift, EMR, Spark, PySpark
- Kinesis, managed Kafka
- SQL, Python
- IAM, CI/CD, infrastructure as code
- Oracle FBDI, JDE
Work location
Protiviti practices a hybrid model combining in-person work with remote work. The ratio of remote to in-person varies by client, project, team, and other business factors. Work may include time in local Protiviti offices and on client sites, with local or out-of-state travel based on project needs.
Starting salary is based on a full-time equivalent schedule. Placement in the range depends on experience, skills, and geo. Total cash range estimate (base plus bonus target opportunity): $140,000 to $224,000.
Additional locations may include Atlanta (Peachtree Rd), Austin, Charlotte, Chicago, Denver, Houston, Miami, Orlando, Philadelphia, Phoenix, and Tampa.
