Lead Database Reliability Engineer at Lifion by ADP
Our industry is starting to go through a transformational shift and we intend to lead it. As talent becomes the main differentiator between failure and success, organizations must attract, engage and develop their people more than ever. To do so, they need powerful and sophisticated tools, which take the pain out of HR management and empower employees & people leaders. That's where we come in.
Lifion by ADP is expanding our startup style operation in NYC in order to accelerate new technical innovation across UI, Search, Platform Technology, IaaS, Big Data, Social, etc. The concept and vision behind the strategy is "Innovate like a Startup" with the goal of delivering highly automated, intelligent and predictive solutions to the market. Our goal is to have specialized teams of superstars focused in these areas to keep pace with market trends and quickly incubate and deliver capabilities that dramatically increase the value of our solutions for clients.
This is a unique role that will combine database automation and some elements of data science. The role will advise on database architecture, tuning, and best practices. Additionally the role will automate common DB maintenance tasks to reduce toil and improve data layer reliability.
In addition to DBRE responsibilities there is an opportunity to work on building some analytics capability to improve visibility into applications problem areas and predict areas that will cause issues for clients in the future.
- A drive to learn and master new technologies and techniques.
- You will use your expertise to tune databases
- You will work closely with other teams to assist them designing, build and fine tune databases, schema design, and query optimizations
- Help automate and build self-service data platform to deliver database as a service to engineering teams.
- Be part of an on-call rotation team.
- Define, track, review and report on Service Level Objectives (SLOs), Service Level Indicators (SLIs), System Availability, and the progress and outcomes related to reliability initiatives.
- Proactively identify opportunities for process improvement.
- Follow up and publish After Action Reviews which are timely and clearly understood by technical and business personnel, and include accurate root causes and concrete follow-up items with clear owners.
- A minimum of 8+ years of any combination in DB, data science, software engineering and/or infrastructure experience.
- Mastery understanding of cloud software, infrastructure, integration and operational ecosystems and product knowledge.
- Mastery knowledge on using MySQL, PostgreSQL databases on the cloud, preferably in AWS
- Familiarity with cloud infrastructure platforms (AWS preferred) and container orchestration technologies
- Expertise in setting up replication, backups, monitoring, Database tuning and SQL tuning.
- A strong familiarity with Continuous Integration and Continuous Deployment methodologies
- Experience with lightweight development methodologies such as Agile - Scrum and / or Kanban
- Experience working with and creating data architectures.
- Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, RedShift etc.
- A plus to have experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.