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We are looking for a Senior Data Engineer to join the Customer Innovation team, who will be responsible for acquiring, transforming, and integrating customer data onto our Data Activation Platform from customers’ clinical, claims, and other data sources. You will work closely with customers to build data and analytics solutions to support their business needs, and be the engine that powers the partnership that we build with them by delivering high-fidelity data assets.

In this role, you will work closely with our Product Managers, Data Scientists, and Software Engineers to build the solution architecture that will support customer objectives. You'll work with some of the brightest minds in the industry, work with one of the richest healthcare data sets in the world, use cutting-edge technology, and see your efforts affect products and people on a regular basis. The ideal candidate is someone that

• Has healthcare experience and is passionate about helping heal people,
• Loves working with data,
• Has an obsessive focus on data quality,
• Is comfortable with ambiguity and making decisions based on available data and reasonable assumptions,
• Has strong data interrogation and analysis skills,
• Defaults to written communication and delivers clean documentation, and,
• Enjoys working with customers and problem solving for them.

A day in the life at Innovaccer:

• Define the end-to-end solution architecture for projects by mapping customers’ business and technical requirements against the suite of Innovaccer products and Solutions.
• Measure and communicate impact to our customers.
• Enabling customers on how to activate data themselves using SQL, BI tools, or APIs to solve questions they have at speed.

What You Need:

• 4+ years of experience in a Data Engineering role, a Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
• 4+ years of experience working with relational databases like Snowflake, Redshift, or Postgres.
• Intermediate to advanced level SQL programming skills.
• Data Analytics and Visualization (using tools like PowerBI)
• The ability to engage with both the business and technical teams of a client - to document and explain technical problems or concepts in a clear and concise way.
• Ability to work in a fast-paced and agile environment.
• Easily adapt and learn new things whether it’s a new library, framework, process, or visual design concept.

What we offer:

• Industry certifications: We want you to be a subject matter expert in what you do. So, whether it’s our product or our domain, we’ll help you dive in and get certified.
• Quarterly rewards and recognition programs: We foster learning and encourage people to take risks. We recognize and reward your hard work.
• Health benefits: We cover health insurance for you and your loved ones.
• Sabbatical policy: We encourage people to take time off and rejuvenate, learn new skills, and pursue their interests so they can generate new ideas with Innovaccer.
• Pet-friendly office and open floor plan: No boring cubicles.

Job Description:

As an Azure Data Engineer, your role will involve designing, developing, and maintaining data solutions on the Azure platform. You will be responsible for building and optimizing data pipelines, ensuring data quality and reliability, and implementing data processing and transformation logic. Your expertise in Azure Databricks, Python, SQL, Azure Data Factory (ADF), PySpark, and Scala will be essential for performing the following key responsibilities:

Designing and developing data pipelines: You will design and implement scalable and efficient data pipelines using Azure Databricks, PySpark, and Scala. This includes data ingestion, data transformation, and data loading processes.

Data modeling and database design: You will design and implement data models to support efficient data storage, retrieval, and analysis. This may involve working with relational databases, data lakes, or other storage solutions on the Azure platform.

Data integration and orchestration: You will leverage Azure Data Factory (ADF) to orchestrate data integration workflows and manage data movement across various data sources and targets. This includes scheduling and monitoring data pipelines.

Data quality and governance: You will implement data quality checks, validation rules, and data governance processes to ensure data accuracy, consistency, and compliance with relevant regulations and standards.

Performance optimization: You will optimize data pipelines and queries to improve overall system performance and reduce processing time. This may involve tuning SQL queries, optimizing data transformation logic, and leveraging caching techniques.

Monitoring and troubleshooting: You will monitor data pipelines, identify performance bottlenecks, and troubleshoot issues related to data ingestion, processing, and transformation. You will work closely with cross-functional teams to resolve data-related problems.

Documentation and collaboration: You will document data pipelines, data flows, and data transformation processes. You will collaborate with data scientists, analysts, and other stakeholders to understand their data requirements and provide data engineering support.

Skills and Qualifications:

Strong experience with Azure Databricks, Python, SQL, ADF, PySpark, and Scala.

Proficiency in designing and developing data pipelines and ETL processes.

Solid understanding of data modeling concepts and database design principles.

Familiarity with data integration and orchestration using Azure Data Factory.

Knowledge of data quality management and data governance practices.

Experience with performance tuning and optimization of data pipelines.

Strong problem-solving and troubleshooting skills related to data engineering.

Excellent collaboration and communication skills to work effectively in cross-functional teams.

Understanding of cloud computing principles and experience with Azure services.

A proficient, independent contributor that assists in technical design, development, implementation, and support of data pipelines; beginning to invest in less-experienced engineers.

Responsibilities:

- Design, Create and maintain on premise and cloud based data integration pipelines. 
- Assemble large, complex data sets that meet functional/non functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.
- Build analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Create data pipelines to enable BI, Analytics and Data Science teams that assist them in building and optimizing their systems
- Assists in the onboarding, training and development of team members.
- Reviews code changes and pull requests for standardization and best practices
- Evolve existing development to be automated, scalable, resilient, self-serve platforms
- Assist the team in the design and requirements gathering for technical and non technical work to drive the direction of projects

Technical & Business Expertise:

-Hands on integration experience in SSIS/Mulesoft
- Hands on experience Azure Synapse
- Proven advanced level of writing database experience in SQL Server
- Proven advanced level of understanding about Data Lake
- Proven intermediate level of writing Python or similar programming language
- Intermediate understanding of Cloud Platforms (GCP) 
- Intermediate understanding of Data Warehousing
- Advanced Understanding of Source Control (Github)

Data Engineer JD:

• Designing, developing, constructing, installing, testing and maintaining the complete data management & processing systems.
• Building highly scalable, robust, fault-tolerant, & secure user data platform adhering to data protection laws.
• Taking care of the complete ETL (Extract, Transform & Load) process.
• Ensuring architecture is planned in such a way that it meets all the business requirements.
• Exploring new ways of using existing data, to provide more insights out of it.
• Proposing ways to improve data quality, reliability & efficiency of the whole system.
• Creating data models to reduce system complexity and hence increase efficiency & reduce cost.
• Introducing new data management tools & technologies into the existing system to make it more efficient.
• Setting up monitoring and alarming on data pipeline jobs to detect failures and anomalies

What do we expect from you?

• BS/MS in Computer Science or equivalent experience
• 5 years of recent experience in Big Data Engineering.
• Good experience in working with Hadoop and Big Data technologies like HDFS, Pig, Hive, Zookeeper, Storm, Spark, Airflow and NoSQL systems
• Excellent programming and debugging skills in Java or Python.
• Apache spark, python, hands on experience in deploying ML models
• Has worked on streaming and realtime pipelines
• Experience with Apache Kafka or has worked with any of Spark Streaming, Flume or Storm

Focus Area:

About Us:

GreedyGame is looking for a Business Analyst to join its clan. We are looking to get an enthusiastic Business Analyst who likes to play with Data. You'll be building insights from Data, creating analytical dashboard and monitoring KPI values. Also you will coordinate with teams working on different layers of the infrastructure.

Job details:

Seniority Level: Associate

Level Industry: Marketing & Advertising

Employment Type: Full Time

Job Location: Bangalore

Experience: 1-2 years

WHAT ARE WE LOOKING FOR?

• Excellent planning, organizational, and time management skills.
• Exceptional analytical and conceptual thinking skills.
• A previous experience of working closely with Operations and Product Teams.
• Competency in Excel and SQL is a must.
• Experience with a programming language like Python is required.
• Knowledge of Marketing Tools is preferable.

WHAT WILL BE YOUR RESPONSIBILITIES?

• Evaluating business processes, anticipating requirements, uncovering areas for improvement, developing and implementing solutions.
• Should be able to generate meaningful insights to help the marketing team and product team in enhancing the user experience for Mobile and Web Apps.
• Leading ongoing reviews of business processes and developing optimization strategies.
• Performing requirements analysis from a user and business point of view
• Combining data from multiple sources like SQL tables, Google Analytics, Inhouse Analytical signals etc and driving relevant insights
• Deciding the success metrics and KPIs for different Products and features and making sure they are achieved.
• Act as quality assurance liaison prior to the release of new data analysis or application.

Skills and Abilities:

• Python
• SQL
• Business Analytics
• BigQuery

WHAT'S IN IT FOR YOU?

• An opportunity to be a part of a fast scaling start-up in the AdTech space that offers unmatched services and products.
• To work with a team of young enthusiasts who are always upbeat and self-driven to achieve bigger milestones in shorter time spans.
• A workspace that is wide open as per the open door policy at the company, located in the most happening center of Bangalore.
• A well-fed stomach makes the mind work better and therefore we provide - free lunch with a wide variety on all days of the week, a stocked-up pantry to satiate your want for munchies, a Foosball table to burst stress and above all a great working environment.
• We believe that we grow as you grow. Once you are a part of our team, your growth also becomes essential to us, and in order to make sure that happens, there are timely formal and informal feedbacks given

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• 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.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.