Technical Project Manager

Roles and Responsibilities

• Managing available resources such as hardware, data, and personnel so that deadlines are met.
• Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
• Exploring data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Defining validation framework and establish a process to ensure acceptable data quality criteria are met
• Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
• Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
• Device self-learning strategies through analysis of errors from the models
• Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
• Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
• Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.

Preferred Technical & Professional expertise

• Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
• At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
• In-depth knowledge of cloud analytics tools.
• Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
• Ability to evaluate hardware selection for running ML models for optimal performance
• Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
• Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
• Deep analytical thinking with excellent problem-solving abilities
• Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
• Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
• Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
• Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards

Summary
Our Kafka developer has a combination of technical skills, communication skills and business knowledge. The developer should be able to work on multiple medium to large projects. The successful candidate will have excellent technical skills of Apache/Confluent Kafka, Enterprise Data WareHouse preferable GCP BigQuery or any equivalent Cloud EDW and also will be able to take oral and written business requirements and develop efficient code to meet set deliverables.

Must Have Skills

• Participate in the development, enhancement and maintenance of data applications both as an individual contributor and as a lead.
• Leading in the identification, isolation, resolution and communication of problems within the production environment.
• Leading developer and applying technical skills Apache/Confluent Kafka (Preferred) AWS Kinesis (Optional), Cloud Enterprise Data Warehouse Google BigQuery (Preferred) or AWS RedShift or SnowFlakes (Optional)
• Design recommending best approach suited for data movement from different sources to Cloud EDW using Apache/Confluent Kafka
• Performs independent functional and technical analysis for major projects supporting several corporate initiatives.
• Communicate and Work with IT partners and user community with various levels from Sr Management to detailed developer to business SME for project definition .
• Works on multiple platforms and multiple projects concurrently.
• Performs code and unit testing for complex scope modules, and projects
• Provide expertise and hands on experience working on Kafka connect using schema registry in a very high volume environment (~900 Million messages)

• Provide expertise in Kafka brokers, zookeepers, KSQL, KStream and Kafka Control center.
• Provide expertise and hands on experience working on AvroConverters, JsonConverters, and StringConverters.
• Provide expertise and hands on experience working on Kafka connectors such as MQ connectors, Elastic Search connectors, JDBC connectors, File stream connector,  JMS source connectors, Tasks, Workers, converters, Transforms.
• Provide expertise and hands on experience on custom connectors using the Kafka core concepts and API.
• Working knowledge on Kafka Rest proxy.
• Ensure optimum performance, high availability and stability of solutions.
• Create topics, setup redundancy cluster, deploy monitoring tools, alerts and has good knowledge of best practices.
• Create stubs for producers, consumers and consumer groups for helping onboard applications from different languages/platforms.  Leverage Hadoop ecosystem knowledge to design, and develop capabilities to deliver our solutions using Spark, Scala, Python, Hive, Kafka and other things in the Hadoop ecosystem. 
• Use automation tools like provisioning using Jenkins, Udeploy or relevant technologies
• Ability to perform data related benchmarking, performance analysis and tuning.
• Strong skills in In-memory applications, Database Design, Data Integration.

• 1-5 years of experience in building and maintaining robust data pipelines, enriching data, low-latency/highly-performance data analytics applications.
• Experience handling complex, high volume, multi-dimensional data and architecting data products in streaming, serverless, and microservices-based Architecture and platform.
• Experience in Data warehousing, Data modeling, and Data architecture.
• Expert level proficiency with the relational and NoSQL databases.
• Expert level proficiency in Python, and PySpark.
• Familiarity with Big Data technologies and utilities (Spark, Hive, Kafka, Airflow).
• Familiarity with cloud services (preferable AWS)
• Familiarity with MLOps processes such as data labeling, model deployment, data-model feedback loop, data drift.

Key Roles/Responsibilities:

• Act as a technical leader for resolving problems, with both technical and non-technical audiences.
• Identifying and solving issues with data pipelines regarding consistency, integrity, and completeness.
• Lead data initiatives, architecture design discussions, and implementation of next-generation BI solutions.
• Partner with data scientists, tech architects to build advanced, scalable, efficient self-service BI infrastructure.
• Provide thought leadership and mentor data engineers in information presentation and delivery.

Recko Inc. is looking for data engineers to join our kick-ass engineering team. We are looking for smart, dynamic individuals to connect all the pieces of the data ecosystem.

What are we looking for:

1. 3+  years of development experience in at least one of MySQL, Oracle, PostgreSQL or MSSQL and experience in working with Big Data technologies like Big Data frameworks/platforms/data stores like Hadoop, HDFS, Spark, Oozie, Hue, EMR, Scala, Hive, Glue, Kerberos etc.

2. Strong experience setting up data warehouses, data modeling, data wrangling and dataflow architecture on the cloud

3. 2+ experience with public cloud services such as AWS, Azure, or GCP and languages like Java/ Python etc

4. 2+ years of development experience in Amazon Redshift, Google Bigquery or Azure data warehouse platforms preferred

5. Knowledge of statistical analysis tools like R, SAS etc 

6. Familiarity with any data visualization software

7. A growth mindset and passionate about building things from the ground up and most importantly, you should be fun to work with

As a data engineer at Recko, you will:

1. Create and maintain optimal data pipeline architecture,

2. Assemble large, complex data sets that meet functional / non-functional business requirements.

3. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

4. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

5. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

6. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

7. Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

8. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

9. Work with data and analytics experts to strive for greater functionality in our data systems.

About Recko: 

Recko was founded in 2017 to organise the world’s transactional information and provide intelligent applications to finance and product teams to make sense of the vast amount of data available. With the proliferation of digital transactions over the past two decades, Enterprises, Banks and Financial institutions are finding it difficult to keep a track on the money flowing across their systems. With the Recko Platform, businesses can build, integrate and adapt innovative and complex financial use cases within the organization and  across external payment ecosystems with agility, confidence and at scale.  . Today, customer-obsessed brands such as Deliveroo, Meesho, Grofers, Dunzo, Acommerce, etc use Recko so their finance teams can optimize resources with automation and prioritize growth over repetitive and time-consuming tasks around day-to-day operations. 

Recko is a Series A funded startup, backed by marquee investors like Vertex Ventures, Prime Venture Partners and Locus Ventures. Traditionally enterprise software is always built around functionality. We believe software is an extension of one’s capability, and it should be delightful and fun to use.

Working at Recko: 

We believe that great companies are built by amazing people. At Recko, We are a group of young Engineers, Product Managers, Analysts and Business folks who are on a mission to bring consumer tech DNA to enterprise fintech applications. The current team at Recko is 60+ members strong with stellar experience across fintech, e-commerce, digital domains at companies like Flipkart, PhonePe, Ola Money, Belong, Razorpay, Grofers, Jio, Oracle etc. We are growing aggressively across verticals.

Role Summary/Purpose:

We are looking for a Developer/Senior Developers to be a part of building advanced analytical platform leveraging Big Data technologies and transform the legacy systems. This role is an exciting, fast-paced, constantly changing and challenging work environment, and will play an important role in resolving and influencing high-level decisions.

Requirements:

• The candidate must be a self-starter, who can work under general guidelines in a fast-spaced environment.
• Overall minimum of 4 to 8 year of software development experience and 2 years in Data Warehousing domain knowledge
• Must have 3 years of hands-on working knowledge on Big Data technologies such as Hadoop, Hive, Hbase, Spark, Kafka, Spark Streaming, SCALA etc…
• Excellent knowledge in SQL & Linux Shell scripting
• Bachelors/Master’s/Engineering Degree from a well-reputed university.
• Strong communication, Interpersonal, Learning and organizing skills matched with the ability to manage stress, Time, and People effectively
• Proven experience in co-ordination of many dependencies and multiple demanding stakeholders in a complex, large-scale deployment environment
• Ability to manage a diverse and challenging stakeholder community
• Diverse knowledge and experience of working on Agile Deliveries and Scrum teams.

Responsibilities

• Should works as a senior developer/individual contributor based on situations
• Should be part of SCRUM discussions and to take requirements
• Adhere to SCRUM timeline and deliver accordingly
• Participate in a team environment for the design, development and implementation
• Should take L3 activities on need basis
• Prepare Unit/SIT/UAT testcase and log the results
• Co-ordinate SIT and UAT Testing. Take feedbacks and provide necessary remediation/recommendation in time.
• Quality delivery and automation should be a top priority
• Co-ordinate change and deployment in time
• Should create healthy harmony within the team
• Owns interaction points with members of core team (e.g.BA team, Testing and business team) and any other relevant stakeholders

• Expertise in designing and implementing enterprise scale database (OLTP) and Data warehouse solutions.
• Hands on experience in implementing Azure SQL Database, Azure SQL Date warehouse (Azure Synapse Analytics) and big data processing using Azure Databricks and Azure HD Insight.
• Expert in writing T-SQL programming for complex stored procedures, functions, views and query optimization.
• Should be aware of Database development for both on-premise and SAAS Applications using SQL Server and PostgreSQL.
• Experience in ETL and ELT implementations using Azure Data Factory V2 and SSIS.
• Experience and expertise in building machine learning models using Logistic and linear regression, Decision tree  and Random forest Algorithms.
• PolyBase queries for exporting and importing data into Azure Data Lake.
• Building data models both tabular and multidimensional using SQL Server data tools.
• Writing data preparation, cleaning and processing steps using Python, SCALA, and R.
• Programming experience using python libraries NumPy, Pandas and Matplotlib.
• Implementing NOSQL databases and writing queries using cypher.
• Designing end user visualizations using Power BI, QlikView and Tableau.
• Experience working with all versions of SQL Server 2005/2008/2008R2/2012/2014/2016/2017/2019
• Experience using the expression languages MDX and DAX.
• Experience in migrating on-premise SQL server database to Microsoft Azure.
• Hands on experience in using Azure blob storage, Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2.
• Performance tuning complex SQL queries, hands on experience using SQL Extended events.
• Data modeling using Power BI for Adhoc reporting.
• Raw data load automation using T-SQL and SSIS
• Expert in migrating existing on-premise database to SQL Azure.
• Experience in using U-SQL for Azure Data Lake Analytics.
• Hands on experience in generating SSRS reports using MDX.
• Experience in designing predictive models using Python and SQL Server.
• Developing machine learning models using Azure Databricks and SQL Server