Responsibilities
- Design and maintain scalable ETL/ELT pipelines that handle both structured and unstructured data.
- Build high-performance data platforms balancing scalability, reliability, and cost efficiency.
- Enhance data storage, processing, and retrieval across modern cloud environments.
- Establish data validation, monitoring, and governance to ensure integrity and regulatory compliance.
- Analyze data to derive insights that inform strategic and operational decisions.
- Provide internal teams with robust data models, metrics, and business intelligence capabilities.
- Translate business requirements into scalable technical solutions, considering constraints.
- Collaborate with stakeholders, analysts, and engineers to deliver enterprise-wide data solutions.
- Model data and prepare datasets for downstream analytics and reporting tools.
- Promote data as a strategic enterprise asset by advancing best practices and standards.
- Contribute to system data standards, governance, and documentation across platforms.
- Explore and implement automated, innovative approaches to improve platform efficiency.
- Design systems that meet performance, scalability, high availability, recoverability, and security requirements.
- Provide technical leadership and mentorship across project teams.
Requirements
- Minimum five years of experience in data engineering, including SQL, data warehousing, and cloud-based data platforms.
- Two or more years in a project lead or supervisory role is preferred.
- Strong expertise with Databricks and modern data ecosystem tools.
- Proficiency in Python, PySpark, and SQL.
- Experience with Delta Lake and Delta Live Tables.
- Knowledge of AWS S3 and cloud storage patterns.
- Experience with columnar formats such as Parquet.
- familiarity with AWS Glue and data pipeline orchestration.
- Experience designing and implementing lakehouse architectures.
- Solid systems analysis skills to translate business needs into technical solutions.
- Strong data modeling and analytics-focused database design capabilities.
- Experience in regulated environments; financial services experience is a plus.
- Excellent problem-solving, troubleshooting, and performance optimization abilities.
- Strong communication skills for engaging both technical and non-technical stakeholders.
- Proven ability to lead initiatives, mentor team members, and influence technical direction.
- Strong time management and prioritization skills in fast-paced environments.
Technologies
- Databricks
- Python
- PySpark
- SQL
- Delta Lake
- Delta Live Tables
- AWS S3
- Parquet
- AWS Glue
Benefits
- Competitive compensation and benefits package
- 401(k) with company match
- Health, dental, and vision insurance
- Life insurance
- Paid time off
- A collaborative, high-integrity work environment with strong leadership
About IQ Ventures
IQ Ventures is an established, profitable technology and financial services company serving clients nationwide. Our Dublin, Ohio office offers a modern, collaborative workspace where innovation thrives. The culture emphasizes high integrity, accountability, and collaboration, valuing both independent thinking and team-driven decision making, guided by leaders with deep industry experience.
Equal Opportunity Employer
IQ Ventures is an Equal Opportunity Employer. We do not discriminate based on race, age, sex or gender, marital status, national origin, disability, religion, sexual orientation, gender identity or expression, veteran status, or other protected statuses. Reasonable accommodations are available for applicants during the hiring process.
Not accepting third-party recruiters at this time
We are not accepting candidates from third-party recruiters at this time.
Job Type
Full-time
Experience
Data Engineering: 1 year (Preferred)
Ability to commute
Dublin, OH 43017 (Required)
Work location
In person
