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Associate Director
2 weeks ago
Position: Associate Director - Data Engineering
Location: Sydney, Australia
Travel: Potential travel within ANZ
Simple Machines. Data Engineered to Life
Simple Machines is a leading independent boutique technology firm with a global presence, including teams in London, Sydney, San Francisco, and New Zealand. We specialise in creating technology solutions at the intersection of data, AI, machine learning, data engineering, and software engineering. Our mission is to help enterprises, technology companies, and governments better connect with and understand their organisations, their people, their customers, and citizens. We are a team of creative engineers and technologists dedicated to unleashing the potential of data in new and impactful ways. We design and build bespoke data platforms and unique software products, create and deploy intelligent systems, and bring engineering expertise to life by transforming data into actionable insights and tangible outcomes.
**We engineer data to life.**
**Requirements**:
Simple Machines is looking to hire a talented Associate Director - Data Engineering to join our cohesive leadership team. This is a full-time role to be based in our Sydney office.
We need you to help us design and deliver a fantastic program of data focused engineering projects for our globally distributed client base.
**About the role**:
You’ll work closely with our Director Client Strategy and our Director Client Delivery to understand client needs and design and successfully deliver compelling market leading solutions. Not only that, you’ll also be a leader of our engineering team, partnering closely with Talent & Culture team to develop and improve our technical professional development programs.
Sound good so far?
**Here’s a brief overview of the role’s responsibilities**:
- Partner with New Business and Client Partners through the pre-sales, sales, and account management process. You’ll respond to client requirements and identify opportunities for their success and continual improvement through their data, and our consulting and engineering.
- Facilitate workshops and client meetings to clearly understand client needs and convert them into compelling technical responses (proposal, solution design, architecture, road maps and more).
- Partner with internal and external engineering teams, delivery leads and the broader business as Technical Leader for consulting, architecture, integration, and software delivery engagements.
- Participate proactively as a member of our Leadership Team, identifying opportunities for business improvement and taking ownership for the delivery of workstreams as part of our business improvement plan.
- Mentor and lead various technical teams, including Technical Leads.
- Establish and maintain relationships with our Vendor Partners (AWS, GCP, Confluent, Lightbend, Immuta and Databricks).
- Engage with our Client Partners to improve and develop new product offerings.
- Partner with Talent & Culture to improve and develop our internal education programs.
**What we need from you as an individual.**:
- Above all, be a great internal and external communicator. You’ll possess a hospitality mindset in managing and engaging collaboratively with all stakeholders, inside and outside the business
- Lead from the front and by example. You’ll take true ownership of tasks, taking responsibility for goals and outcomes.
- Act as an excellent role model for your peers and the entire Simple Machines team
- Bring a genuine fit-for-purpose mindset to everything that you do.
- Strong architecture, engineering, client engagement and communication skills are an absolute must.
- Demonstrate a genuine passion for technology and continually learning - a growth mindset that believes there is always, always more to know.
- Exhibit a humble, low-ego attitude.
**The technology experience we’re looking for.**:
**Ideally you will have experience in the following areas**:
- Architecting contemporary enterprise data platforms.
- Contemporary cloud platforms. (AWS, GCP, Azure)
- Modern dev ops practices. (docker/kubernetes)
- Contemporary data processing technologies (Spark, Flink, others) and concepts.
- Data governance, monitoring and lineage.
- Awareness and potential experience with machine learning, decisioning system, rules engines, analytics.
- The broader ecosystem of data related technologies.