About talentflow
At talentflow, we’re redefining the way data powers innovation across the entertainment and technology sectors. With a global footprint that spans from cutting‑edge streaming platforms to immersive digital experiences, talentflow harnesses the full potential of data to create unforgettable moments for millions of users worldwide. Our culture is built on curiosity, collaboration, and a relentless pursuit of excellence. We empower our teams to experiment, iterate, and deliver solutions that transform raw information into actionable insights.
Position Overview
We’re looking for a seasoned Lead Data Engineer to spearhead the design, development, and maintenance of our next‑generation data infrastructure. In this pivotal role, you will partner with product managers, data scientists, and software engineers to build scalable, high‑performance data pipelines that support talentflow’s ambitious growth plans. If you thrive in a fast‑paced, agile environment and have a passion for turning complex data challenges into elegant, production‑ready solutions, we want to hear from you.
Key Responsibilities
- Architect and Build Data Solutions: Design robust data warehouses, lakehouses, and real‑time streaming pipelines that support talentflow’s diverse product portfolio.
- Lead End‑to‑End ETL Development: Build and optimize ETL workflows across cloud, on‑premises, and hybrid environments using modern tools such as Airflow, dbt, and Spark.
- Data Modeling & Governance: Collaborate with data architects and modelers to define semantic layers, master data models, and enforce data quality standards.
- Cross‑Functional Collaboration: Work closely with product owners, data scientists, and business stakeholders to translate requirements into scalable data solutions.
- Documentation & Knowledge Sharing: Maintain comprehensive documentation of data pipelines, schemas, and best practices to ensure knowledge continuity.
- Performance & Reliability: Monitor pipeline health, troubleshoot failures, and implement SLAs to guarantee high availability and data integrity.
- Agile Leadership: Mentor junior engineers, facilitate sprint planning, retrospectives, and champion continuous improvement practices.
- Innovation & Thought Leadership: Stay abreast of emerging data technologies, evaluate new tools, and propose architectural enhancements that drive efficiency.
Essential Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s preferred).
- 10+ years of experience in data engineering, with at least 4 years in a leadership capacity.
- Proven expertise in SQL and experience building complex queries for large datasets.
- Hands‑on experience with distributed processing frameworks such as Hadoop, Spark, or Flink.
- Deep knowledge of cloud data platforms (AWS, GCP, or Azure) and MPP databases (Snowflake, Redshift, BigQuery).
- Strong programming skills in Python, Java, or Scala.
- Experience designing and maintaining data pipelines using orchestration tools (Airflow, Prefect, Dagster).
- Familiarity with data modeling best practices (star/snowflake schemas, dimensional modeling).
- Solid understanding of data governance, security, and compliance frameworks.
- Excellent communication skills and a collaborative mindset.
Preferred Qualifications
- Experience with real‑time streaming technologies (Kafka, Kinesis, Pub/Sub).
- Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines for data workloads.
- Background in machine learning pipelines or data science workflows.
- Certifications in cloud platforms (AWS Certified Data Analytics, GCP Professional Data Engineer).
- Prior experience in a high‑growth, consumer‑facing tech company.
Skills & Competencies
- Strategic thinking and the ability to translate business objectives into technical roadmaps.
- Strong analytical mindset with a knack for troubleshooting complex data issues.
- Leadership and mentorship capabilities, fostering growth in junior team members.
- Adaptability to rapidly evolving technologies and shifting priorities.
- Commitment to data quality, security, and ethical data practices.
Career Growth & Learning Opportunities
At talentflow, your professional development is a top priority. You’ll have access to:
- Annual learning stipend for courses, conferences, and certifications.
- Mentorship programs pairing you with senior leaders across the organization.
- Opportunities to lead cross‑functional initiatives and shape talentflow’s data strategy.
- Internal mobility pathways to roles in data science, product management, and engineering.
- Regular hackathons and innovation challenges to experiment with new ideas.
Work Environment & Culture
Our culture is built on transparency, inclusivity, and a shared passion for data. You’ll find:
- Remote‑first flexibility with optional on‑site collaboration in our San Francisco hub.
- Weekly tech talks, lunch & learn sessions, and a vibrant community of data enthusiasts.
- A collaborative, flat hierarchy that encourages open dialogue and rapid decision‑making.
- Commitment to work‑life balance, with generous vacation policies and mental health resources.
Compensation & Benefits
While the base salary for this role starts at $24 per hour, talentflow offers a comprehensive benefits package that includes:
- Competitive base salary and performance‑based bonuses.
- Health, dental, and vision insurance with generous coverage.
- 401(k) plan with company match.
- Unlimited paid time off and flexible working hours.
- Wellness stipend, on‑site gym access, and mental health support.
- Employee stock purchase plan and equity options.
How to Apply
Ready to join talentflow and lead the next wave of data innovation? Submit your resume and a brief cover letter outlining your experience and why you’re excited about this role. We’re eager to meet talented individuals who are ready to make an impact.
Apply for this job