1001 – 5000 Darbinieki
Kvalificēta darbinieka vīzas sponsorsAnalītikaKonsultācijasMākslīgais intelektsSDG Group ir globāls konsultāciju uzņēmums, kas specializējas datos, analītikā un mākslīgajā intelektā. Uzņēmums, kas dibināts 1994. gadā, palīdz organizācijām pārvērst sarežģītus datus praktiskās biznesa atziņās, apvienojot procesu pārvaldības kompetenci ar vadošo programmatūras piegādātāju progresīvām tehnoloģijām un analītikas platformām. SDG Group atbalsta klientus uz datiem balstītā pārveidē un inovāciju īstenošanā, un tajā dažādās starptautiskās vietās strādā vairāk nekā 2 000 konsultantu. Karjeras iespējas ietver personīgās un profesionālās izaugsmes iespējas elastīgā darba modelī, kas izstrādāts darba un privātās dzīves līdzsvara atbalstam.
Senior Databricks Data Engineering Consultant
Lead client data engineering delivery at SDG Group, building scalable Databricks solutions and optimizing SQL transformations. Guide technical decisions, mentor colleagues, and help clients connect cloud data platforms to business outcomes.
Apraksts
- Build and maintain scalable data solutions on Databricks through design, testing, and ongoing support.
- Improve complex SQL queries and transformation logic by troubleshooting and tuning performance.
- Lead data engineering workstreams and make informed technical decisions.
- Connect structured and unstructured data sources with ETL/ELT methods and integration tools.
- Design and review scalable data models and warehouse structures for reporting, analytics, AI, and downstream use.
- Contribute to cloud data platform architecture and modernization.
- Set strong delivery practices for development, testing, documentation, deployment, maintainability, and governance.
- Resolve and improve data quality, reliability, scalability, and query or pipeline performance issues.
- Work with client stakeholders to clarify needs, explain tradeoffs, recommend solutions, set technical expectations, and tie engineering choices to business results.
- Coordinate with multidisciplinary teams, review technical work, share practices, and mentor junior engineers and consultants.
- Keep up with Databricks features, data engineering methods, and industry practices.
- Share expertise and provide technical leadership across the SDG community.
Prasības
- Bring approximately 5–7 or more years of experience in data engineering, data warehousing, data integration, analytics engineering, or a related technical field.
- Show a track record of owning complex technical delivery.
- Have extensive professional, hands-on Databricks experience, including production data engineering and analytics workloads.
- Use Databricks SQL at an advanced level.
- Apply advanced SQL skills across joins, CTEs, window functions, aggregations, complex transformations, performance tuning, and data validation.
- Work confidently in Python or another relevant programming or scripting language.
- Understand data pipelines, ETL/ELT, integration, warehousing, transformation patterns, and production data engineering practices in depth.
- Understand dimensional modeling and modern data modeling concepts.
- Have strong experience with modern cloud environments and enterprise-scale data platforms.
- Have worked with modern data engineering, orchestration, or transformation tools.
- Lead data validation, reconciliation, troubleshooting, and performance tuning across multiple source and target systems.
- Apply sound analytical and architectural judgment.
- Communicate effectively in writing and conversation.
- Lead technical discussions, influence stakeholders, explain complex topics clearly, and earn client trust.
- Mentor colleagues and continue developing technical and consulting skills.
- Consulting or other client-facing experience is strongly preferred.
- Experience with Matillion and/or dbt is highly preferred.
- Preferred experience includes Databricks SQL Warehouses, Delta Lake or Delta Tables, Databricks Workflows, Unity Catalog, Snowflake, PySpark, and large-scale enterprise data migration or modernization.
- Experience in pharmaceuticals, life sciences, healthcare, or another highly regulated sector is preferred.
Priekšrocības
- Full-time work in a growing high-tech sector.
- A merit-based culture that supports career progression and professional growth.
- Competitive pay.
- 401(k) retirement plan with employer matching.
- Medical, dental, vision, and disability coverage.
- At least three weeks of paid vacation.
- Flexible holiday schedule.
- Hybrid work combining on-site and remote arrangements.
- Ongoing training and experience with modern data, analytics, and AI technologies.
- A collaborative workplace alongside experienced professionals.
- Substantive client projects.