Searce Inc
Website:
searce.com
Company:
https://www.linkedin.com/company/searceinc
Seniority: Mid-Senior level
Industries: IT Services and IT Consulting
Job details:
Manager - Data Engineering
What are we looking for
real solver?
Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.
Your Mission: The Role
solving for better.
Are you a hands-on technical manager who thrives on cracking high-octane data platform challenges? The Modern Data & AI Engineering BU is looking for a Mid-Senior Manager, Data Engineering to join our elite Solver Squad as a Lead Forward Deployed Solver (FDS).
The Solver Squad is a core group of expert engineers responsible for tackling our most complex client data projects, building mission-critical internal platforms, and setting the standard for technical excellence. As a Mid-Senior Manager, you aren't a "people manager" who sits in spreadsheets—you are a Playing Captain on the field, architecting scalable data platforms, committing code, and mentoring an elite pod of engineers to deliver high-impact AI transformations.
Your Responsibilities
What you will wake up to solve.
- Architect & Build Hands-On: Design, build, and optimize scalable, cloud-native data platforms. You will remain 100% hands-on-keys—building, breaking, and perfecting high-velocity pipelines alongside your squad using Python, SQL, Spark, and Airflow.
- Mentor & Elevate the Squad: Lead and inspire a pod of Data Engineers and Architects. You'll drive deep-dive code reviews, elevate engineering standards, enforce modern CI/CD data practices, and take direct ownership of your team's technical growth and delivery velocity.
- Partner with Clients as Technical DRI: Act as the Directly Responsible Individual (DRI) for enterprise clients. You will navigate complex cross-cloud environments across Snowflake, Databricks, BigQuery, AWS, and GCP, translating ambiguous client visions into actionable, high-impact engineering roadmaps.
- Engineered for AI-Readiness: Design modern data structures and clean room environments engineered specifically to fuel Machine Learning, Advanced Analytics, and Generative AI applications.
- Troubleshoot & Optimize for Scale: Own the performance, cost-efficiency, and resilience of the reporting and analytics layer. You will proactively identify bottleneck transformations and tune architectures to run faster, cheaper, and cleaner.
- Innovate & Build Reusable IP: Spearhead the creation of custom operators, automated framework accelerators, and proprietary data libraries to give Searce a distinct technical edge in the market.
Functional Skills
- The Playing Captain: This persona leads from the front by writing production-grade code, jumping directly into the terminal during critical outages, and setting the technical bar high for the entire squad.
- The Solution Architect: Deconstructs complex, ambiguous client problems into clear, scalable, and multi-cloud technical designs. They translate strategy into concrete data blueprints—from schema design to partitioning strategies—foreseeing technical bottlenecks and making pragmatic trade-offs.
- The Pragmatic Innovator: Balances a passion for modern technology (GenAI enablement, real-time streaming) with a sharp focus on business outcomes. They champion tools that add real value while ensuring systems remain cost-effective, robust, and delivered on schedule.
- The Client-Facing Technologist: Serves as the crucial technical bridge between the data squad and executive stakeholders. They build trust by explaining complex technical concepts (like latency vs. cost, schema evolution, or idempotency) in simple terms that align with strategic business goals.
- The Quality Craftsman: Possesses an unwavering commitment to excellence and treats data engineering as a high-stakes craft. They act as the guardian of the reporting layer, advocating for robust testing, automated monitoring, secure practices, and clean code to ensure long-term platform health.
Proven Experience
- Engineering & Leadership Depth: 8+ years of hands-on experience in Data Engineering and Architecture, with at least 2+ years leading engineering pods or squads in high-velocity, fast-paced environments.
- Cloud-Native & Platform Mastery: Deep fluency in designing and deploying production-grade data solutions on public cloud platforms (GCP, AWS, Azure) and modern data stack engines (BigQuery, Snowflake, Databricks, Spark, Kafka, Airflow).
- AI-Native Expertise: Demonstrable experience building data foundations specifically geared toward supporting AI/ML initiatives, alongside proficiency in using AI coding assistants (e.g., GitHub Copilot) to accelerate daily workflows.
- Business Impact & Transformation: A proven track record of leading 2–3 large-scale enterprise data initiatives—such as platform migrations, data lakehouse builds, or real-time analytics architectures—that deliver measurable outcomes.
- Client-Facing Acumen: Direct experience in a consultative, client-facing role, with the confidence to translate a CEO's business vision into precise technical specifications without losing anything in translation.
Join the ‘real solvers’
ready to futurify?
If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.
Click on Apply to know more.
