Data Operations Engineer
- Lead day-to-day operations to ensure organizational delivery of quality results.
- Responsible for provisioning, enabling, scaling and maintaining our team's data, analytics and ML infrastructures for batch and real time systems including pipelines, frameworks, tools and services in hybrid cloud.
- Shepherd zero-downtime deployment process through continuous delivery practices, rapidly releasing features that provide critical and faster insights to business users.
- Collaborate with the platform team by building the right tools for observability , monitoring, alerting and self-healing for the day to day management of analytics foundations.
- Debug complex problems in distributed environment and ability to run the prod incidents efficiently to following up with Post incident reviews.
- Developing self-service tools and automation to improve engineering efficiency and the quality of services.
- Excellent verbal and written communication skills.
- Self-starter with forward thinking capability with strong executional track record and be accountable for business priorities.
- Hands-on experience with CI/CD pipelines and cloud environments like Gitlab, Spinnaker, Docker/Kubernetes observability using Splunk, Grafana/Data dog is a huge plus.
- Proficient with one or more programming languages such as Python/Go/Rust/Java/Scala for automation and API integrations.
- Experience in implementing security controls, governance processes, compliance validation, infrastructure cost analysis and optimization.
- Knowledge of analytics and Applied ML stack like Apache Spark, Trino/Pinot, Iceberg, Atlas, Flink, Airflow/Luigi, Tableau, Snowflake, Databricks, MLFlow, Data Catalogs, Jupyter Notebooks, Vector database and Cassandra.
- Solid understanding of IAAC (infrastructure as a code) techniques like terraform, orchestration and tooling.
- Experience scaling operations in a fast-paced and dynamic environment. Experience working in agile or evolving product environments."
- Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
- Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes
- 10+ years of demonstrated experience in an Analytics and Strategy role.
- Strong business acumen and the ability to think strategically and operationally.
- Be a self-starter, driven, accountable and a high-energy team player.
- Proven experience being a thought partner to cross-functional business teams offering actionable data insights and recommendations.
- Demonstrated ability to influence without authority.
- Excellent communication skills-able to distill complex analysis into simple, compelling narratives. Background in consulting or customer-facing, fast-paced analytical environment.
- Expertise with SQL, R or Python and data visualization tools such as Tableau for full-stack data analysis, insight synthesis and presentation.
- Knowledge of and experience in leveraging Applied Statistical/ML techniques.
- Bachelor's degree in Economics, Finance, Statistics, Mathematics, Econometrics, or Applied Social Sciences.
- Limited immigration sponsorship may be available
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
- Hybrid role - On-site Tue-Wed-Thu
- 15+ years of demonstrated experience in an Analytics and Strategy role, preferably in the payments/fintech domain.
- Ability to understand ambiguous and complex problems and design and execute analytical approaches and turn analysis into clear and concise takeaways that drive action.
- Track record of leading organization-wide strategic initiatives or transformative analytics projects.
- Master's degree in Economics, Finance, Statistics, Mathematics, Econometrics, or Applied Social Sciences.
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