Head - Data Engineering & Analytics - IT

Job Description

Key Responsibilities: Manage Data: - Building the next generation extremely large, scalable and fast distributed systems to ingest, organise and manage all data at scale efficiently- Own and optimize data architecture to address the data needs of our rapidly-growing business- Setup, manage & maintain data lakes and warehouses across the entire organisation- Setup, manage & maintain BI solutions & tools to analyse data- Setup data streaming systems to ingest and automate data at scale- Ensure quality and workability of all data Analyse Data: - Architect, build, and launch new data models that provide intuitive analytics to various teams across multiple tech stacks- Build and integrate robust data processing pipelines for enterprise-level business analytics- Work with customers of the data team in a fast paced environment understanding the business requirements and implementing analytical solutions. Work with engineering, product and business owners to develop and define key business questions and to build data sets that answer those questions- Assist other team members with reporting, debugging data accuracy issues and other related functions Model Data: - Leverage the understanding developed by introspecting the data to build data models for product functioning and product enhancement- Build predictive data models for recommendation, classification etc- Identify the right model for every use case - simple empirical model to a deep learning based model and everything in between- Devise strategies to test and trial run the models built- Continuously monitor the performance of models and enhance- Own the entire process end to end from data collection, cleaning, feature engineering, algorithm/tool selection, model testing to the final model Deploy Data: - Translate data models into efficient engineering code to deploy at scale efficiently- Build systems for the product to leverage data and models based on the data in real time- Meticulously develop and deploy production data pipelines (batch + real time)- Analyse on models decision data, to deepen intuition, for best integration of machine learning model recommendations- Skill fully implement performance engineering of relevant big data systems- Building a team which is thoughtfully developing, improving, and owning data systems that empowers the entire organisation with data- Lead and provide coaching to the data engineering team. Lead by example, demonstrating best practices for unit testing, CI/CD, performance testing, capacity planning, documentation, monitoring, alerting, and incident response- Actively participate in key business, architectural and technical decisions Desired Candidates Profile: - Relevant Experience in a data focused role - 5+ years- Strong hold on SQL- Prior experience of building a data lakes / warehouses- Strong background in new age AWS stack (S3, EMR, Redshift) or traditional BI & DW with interest in data mining and ability to sieve emerging patterns and trends from large amount of data.- Experience with data modeling, data warehousing, and building ETL pipelines- Extensive experience in dimensional modeling, excellent problem solving ability dealing with huge volumes of data and a short learning curve- Experience in analyzing data to draw business-relevant conclusions and in data visualization- Experience leading and influencing the data strategy of your team or organization- Strong written and verbal communication skills including technical writing skills- Strong background in statistical concepts and calculations Innovative and strong analytical and algorithmic problem solvers.- Experience with modern data warehousing products like Redshift, Bigquery, Snowflake.- Proficiency with analysis tools like Excel, SQL, Python (Knowhow of AWS infra is a plus point)- Acquaintance with concepts of BI - MicroStrategy, QlikSense, Tableau- Experience working with Big Data streaming services such as Kinesis, Kafka etc- Experience working with NoSQL data stores such as HBase, Mongo etc- Experience working with Hadoop or Big Data processing frameworks (Spark, Hive, Nifi, Spark-Streaming, Flink, etc.)- Advanced Excel & VBA scripting- Excellent coding skills in Scala or Python- Experience with data science libraries such as Scikit-learn, Pandas, Numpy, Scipy, Spacy, NLTK, H2O, Tensorflow and Pytorch.- Team HandlingImmediate joiners will be highly appreciated.Interested Candidate may reach out directly on +91 99hidden_mobile5 for quick call,

Keyskills :
data warehousinginformaticapythonnew agejava