Data Engineer

Responsibilities :

- Proficiency in SQL database design, proficiency in creating process documentation, strong written and verbal communication skills, and the ability to work independently and on teams.

- Familiarity with the computer coding languages python, java, kafka, hive, or storm may be required in order to oversee real-time business metric aggregation, data warehousing and querying, schema and data management, and related duties.

- Should have knowledge of algorithms, data structures, and performance optimism and experience with processing and interpreting data sets.

- Develop technical solutions to improve access to data and data usage.

- Understand data needs and advise company on technological resources.

- Aggregate and analyze various data sets to provide actionable insight.

- Develop reports, dashboards, and tools for business-users.

Key Responsibilities :

- Lead, mentor, and inspire a high-performing team of Data Scientists, Analysts, and AI/ML Engineers, fostering a collaborative, innovative, and impact-driven environment.

- Design, develop, and maintain robust data models, analytics frameworks, dashboards, and machine learning solutions that drive business strategy and decision-making.

- Develop and execute experimentation frameworks, including defining clear success metrics, designing A/B tests, and analyzing results to guide strategic product decisions.

- Partner closely with product, engineering, and leadership to translate complex clickstream behavioral data into strategic insights that inform product roadmaps and investments.

- Clearly communicate findings, insights, and recommendations to both technical and non-technical stakeholders, building credibility and driving alignment with senior leadership.

- Influence product direction by developing hypotheses, employing analytical rigor, and creating clear, impactful presentations and narratives around data-driven insights.

- Continuously identify new opportunities for leveraging data and analytics to enhance product capabilities, operational efficiency, and customer satisfaction.

- Drive measurement strategies, set ambitious goals, forecast outcomes, and closely monitor key product and business metrics.

Requirement :

- 5+ years of technical experience in data analytics, data engineering, data science, or AI/ML.

- Proven experience working extensively with behavioral clickstream data, experimentation (A/B testing), and statistical analysis.

- Advanced expertise in data modeling, data design, and creating analytics strategies aligned with complex business needs.

- Extensive experience collaborating cross-functionally with product management, engineering, and senior leadership.

- Outstanding communication skills, with the ability to translate technical concepts into clear narratives and actionable insights for diverse audiences.

- Demonstrated ability to navigate ambiguity, prioritize effectively, and execute in a dynamic, fast-paced environment.

- Expert proficiency in SQL/Hive, Python or R, with substantial experience querying, analyzing, and building models on large-scale datasets.

- Strong product sense with the ability to identify and quantify opportunities, define clear success metrics, and shape strategic priorities.

- Track record of driving innovation, influencing product roadmaps, and delivering measurable business impact through data-driven initiatives