3 Structured Data Jobs

Shopify Front-End Developer Performance & SEO Optimization Location: Bangalore, Bannerghatta Road Work Mode: 5 Days Work From Office (WFO) No remote or hybrid options Joining Preference: Looking for early joiners About the Role We are looking for a mid to senior level Shopify Front End Developer to join our fast-paced ecommerce team. This role is 50% development and 50% performance/SEO optimization. It is ideal for someone who thrives in a dynamic environment and understands Shopifys frontend architecture, Liquid templating, and site speed best practices. Responsibilities Front-end Development (50%) Customize and maintain Shopify themes using Liquid, HTML, CSS, and JavaScript Work closely with design and content teams to create high converting user experiences Develop custom sections, features, and micro-interactions to enhance engagement Implement A/B testing and data-driven updates to improve UX and conversion Performance & SEO Optimization (50%) Optimize site speed, core web vitals, and responsive performance across mobile and desktop Audit and implement onsite SEO best practices, including schema markup, image optimization, meta structures, and link architecture Evaluate third party apps for performance impact and recommend code-based solutions Use tools like Lighthouse, GTmetrix, Google Search Console, and Semrush to measure and enhance site health Collaborate with marketing and content teams to ensure technical SEO aligns with overall strategy Qualifications 35+ years of frontend development experience, ideally in ecommerce 3+ years of hands-on work in the Shopify ecosystem (theme development & customizations) Strong knowledge of Liquid, HTML5, CSS3, JavaScript (Vanilla, Alpine.js, React) Deep expertise in performance optimization & technical SEO within a Shopify environment Experience with Git, browser dev tools, and page speed tools (Lighthouse, Semrush) Excellent communication and collaboration skills across teams Bonus: Familiarity with headless commerce or Shopify Hydrogen

Data Analyst Location: Bangalore Experience: 8 - 15 Yrs Type: Full-time Role Overview We are seeking a skilled Data Analyst to support our platform powering operational intelligence across airports and similar sectors. The ideal candidate will have experience working with time-series datasets and operational information to uncover trends, anomalies, and actionable insights. This role will work closely with data engineers, ML teams, and domain experts to turn raw data into meaningful intelligence for business and operations stakeholders. Key Responsibilities Analyze time-series and sensor data from various sources Develop and maintain dashboards, reports, and visualizations to communicate key metrics and trends. Correlate data from multiple systems (vision, weather, flight schedules, etc) to provide holistic insights. Collaborate with AI/ML teams to support model validation and interpret AI-driven alerts (e.g., anomalies, intrusion detection). Prepare and clean datasets for analysis and modeling; ensure data quality and consistency. Work with stakeholders to understand reporting needs and deliver business-oriented outputs. Qualifications & Required Skills Bachelors or Masters degree in Data Science, Statistics, Computer Science, Engineering, or a related field. 5+ years of experience in a data analyst role, ideally in a technical/industrial domain. Strong SQL skills and proficiency with BI/reporting tools (e.g., Power BI, Tableau, Grafana). Hands-on experience analyzing structured and semi-structured data (JSON, CSV, time-series). Proficiency in Python or R for data manipulation and exploratory analysis. Understanding of time-series databases or streaming data (e.g., InfluxDB, Kafka, Kinesis). Solid grasp of statistical analysis and anomaly detection methods. Experience working with data from industrial systems or large-scale physical infrastructure. Good-to-Have Skills Domain experience in airports, smart infrastructure, transportation, or logistics. Familiarity with data platforms (Snowflake, BigQuery, Custom-built using open-source). Exposure to tools like Airflow, Jupyter Notebooks and data quality frameworks. Basic understanding of AI/ML workflows and data preparation requirements.

Role & responsibilities: Delivery of Key Projects : Successfully deliver advanced analytics and data science projects within predefined timelines and budget constraints. Collaboration : Collaborate effectively with data engineers and ML engineers to comprehend data and models, utilizing various advanced analytics capabilities. Solution Development : Develop efficient solutions for complex problems, showcasing expertise in data structures like Delta/Parquet, databases, data analytics, Python programming, and statistics. End-to-End Pipeline Management : Manage the entire data science pipeline, including problem scoping, data gathering, modeling, insights generation, visualizations, monitoring, and maintenance. Dashboard Design : Design dashboards using Python Dash (plotly) or Flask framework for effective data visualization and reporting. Technological Expertise : Utilize CI/CD tools, data pipeline technologies, and visualization/data storytelling tools proficiently. ETL Pipeline Building : Construct ETL pipelines using Python or Azure Synapse to facilitate efficient data processing and management. Data Procurement and Management : Independently procure and process data, ensuring seamless integration within the company's overall data management strategy. Technology Exploration : Continuously monitor advancements in artificial intelligence technology and identify applications for problem-solving within the company. Technical Skills: Proficiency in Python and common libraries ( Dash, Pandas, Scikit-Learn, Pydantic, TensorFlow ). Strong Knowledge in Statistics and Probability . Set up cloud alerts, monitors, dashboards, and logging systems, and troubleshoot data platform infrastructure as needed. Experience in OpenShift/Kubernetes, Azure ML is desirable. Proficiency in programming languages: Python (Dash) and database query languages SQL or KQL . Good applied statistical skills, including hands-on experience in time series modeling, predictive modeling, distributions, and regression . Knowledge of DevOps/MLOps . Exceptional analytical and problem-solving skills. Desired candidate profile : Bachelor's or Master's degree in Computer Science or a related technical field, or equivalent experience. Total of 6 to 10 years of professional experience. Minimum 4 years of experience in data science/machine learning . Minimum 3 years of experience with SQL . Experience in DevOps, preferably with hands-on experience in one or more cloud service providers, with Azure being preferred. If the above has triggered your interest, we are looking forward to receiving your application! ** Data Analyst/ Data Engineer profiles are not suitable for this role. Looking for core experience with a Data Scientist role only.