BI Looker

🚨 Hiring: MicroStrategy Developer

We are looking for an experienced MicroStrategy Developer for a 6-month contract opportunity.

📌 Role: MicroStrategy Developer

💼 Experience: 5+ Years

📍 Location: Bangalore / Hyderabad / Mumbai / Delhi

🏢 Work Mode: Onsite

📅 Contract: 6 Months

Key Requirements:

• 5+ years of hands-on MicroStrategy experience

• Strong experience in MicroStrategy development

• Strong SQL skills

• Experience in BI reporting and dashboard development

• Experience with data warehousing and analytics

• Ability to understand business requirements and develop reporting solutions

• Experience in troubleshooting and supporting MicroStrategy applications

Interested candidates can apply with their updated resume.

Data Engineer – Contract Opportunity

We are looking for an experienced Data Engineer with 5+ years of experience to work on subscriber activation, churn, FTE, and future reporting requirements.

Key Responsibilities:

• Work on data requirements related to Subscriber Activation, Churn, FTE, and future reporting.
• Work with BigQuery as the centralized data warehouse.
• Develop and maintain data ingestion and integration pipelines across multiple source systems.
• Design and implement ETL/ELT processes.
• Develop data models for reporting and analytics.
• Integrate BigQuery with Power BI or similar reporting tools.

Required Skills:

• Strong hands-on experience with GCP & BigQuery
• Data warehouse architecture, design, and implementation
• Data ingestion/integration across multiple source systems
• ETL/ELT and data pipeline development
• Data modelling for reporting and analytics
• Experience integrating BigQuery with Power BI or similar reporting tools

Contract: 1 month initially, with potential extension

Compensation: ₹6–7 LPA

Work Mode: Remote

Important

Since this is only a 1-month contract, mention “Potential extension” rather than saying it will definitely be extended.

Strong Data Analyst Profile with Python, SQL, and data-pipeline expertise, ideally with retail / e-commerce datasets

2

Mandatory (Experience 1): Must have 4+ years of hands-on data-analyst experience, working with large datasets across areas such as sales, inventory, pricing, promotions, and customer behaviour.

3

Mandatory (Tech skill 1): Must have strong hands-on Python for data processing, transformation, automation, and analysis

4

Mandatory (Tech skill 2): Must have strong SQL skills, including complex queries, joins, aggregations, and data validation.

5

Mandatory (Tech skill 3): Must have a solid understanding of Data Lake architecture, ingestion, storage, and processing workflows

6

Mandatory (Tech skill 4): Must have hands-on experience with ETL / ELT pipelines, data integration, and transformation

7

Mandatory (Tech skill 5): Must have experience with Azure or GCP data services.

8

Mandatory (Tech skill 6): Must have understanding of or experience with Databricks and distributed data processing.

9

Mandatory (Tech skill 7): Must have knowledge of data modeling, data warehousing, and Lakehouse architecture

10

Mandatory (Tech skill 8): Must have experience with Power BI, Tableau, or Excel for reporting.

11

Mandatory (Communication): Must have strong analytical, documentation, and stakeholder-communication skills.

12

Mandatory (Education): Must hold a Bachelor’s degree in Computer Science, IT, Engineering, or a related field.

13

Mandatory (Note1): This is a 6-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)

Data Engineer

Experience - 5+ years

6-7 LPA

Remote

Duration: 1 month contract (We can take as a tentative, It can be extended)

Scope: Subscriber Activation, Churn, FTE and future reporting requirements, with BigQuery as the centralized data warehouse and Power BI as the proposed reporting layer.

Key Skills:

Strong hands-on experience with GCP & BigQuery

Data warehouse architecture, design and implementation

Data ingestion/integration across multiple source systems

ETL/ELT and data pipeline development

Data modelling for reporting and analytics

Experience integrating BigQuery with Power BI or similar reporting tools

Job Title: Senior Data Engineer

Position Summary

We are seeking a highly skilled Data Engineer with strong expertise in reporting infrastructure, data modeling, and analytics platforms. This role will focus on building scalable reporting solutions, optimizing data pipelines, and enabling data-driven decision-making across the organization. The ideal candidate will have deep experience with databases, data warehousing, and complex query development. While Ruby on Rails experience is beneficial, the primary emphasis is on data engineering and reporting systems.

Key Responsibilities

• Design, develop, and maintain reporting infrastructure and data platforms.
• Build and optimize complex SQL queries, data models, and reporting datasets.
• Develop scalable ETL/ELT pipelines and data integration processes.
• Design and maintain database schemas to support analytics and reporting requirements.
• Collaborate with business stakeholders to understand reporting needs and translate them into technical solutions.
• Implement data quality, governance, and performance best practices.
• Support and enhance enterprise reporting solutions and dashboards.
• Work with large-scale datasets in cloud data warehouse environments.
• Troubleshoot reporting issues and optimize database performance.
• Partner with engineering and product teams to establish sustainable data architecture.

Must Have: Technical Skills

• PostgreSQL
• Snowflake
• Advanced SQL
• Data Modeling
• Data Warehousing
• Reporting & Analytics Infrastructure
• ETL/ELT Development
• Query Performance Tuning

Success Profile:

The ideal candidate is a data-focused engineer who enjoys working with complex datasets, designing scalable reporting solutions, and building foundational infrastructure that empowers analytics and business intelligence teams. They should be comfortable navigating databases, optimizing queries, and translating business reporting needs into robust technical implementations.

Experience Range: 5-10 years

Role Type: Individual Contributor / Senior Engineer

Primary Focus: Reporting Infrastructure, Data Engineering, Data Warehousing, and Analytics Enablement.

Key Skills

Advanced hands-on experience in Alteryx Designer.

Strong knowledge of Alteryx workflows, Macros (Standard, Batch & Iterative).

Excellent SQL skills, including complex queries, joins, CTEs and aggregations.

Strong experience in ETL/ELT, data transformation and integration.

Alteryx workflow performance optimization and troubleshooting.

Experience with Alteryx Server / Alteryx One administration.

Production support, workflow scheduling and deployment.

Knowledge of Snowflake, SQL Server and PostgreSQL.

Microsoft Entra ID and SCIM provisioning knowledge is preferred.

Excellent communication and stakeholder management skills.

Mandatory Requirements

Valid Alteryx Designer Core Certification or higher is mandatory.

Strong hands-on experience in Alteryx workflow development.

Practical experience with Alteryx Macros.

Strong SQL and ETL/ELT expertise.

Experience in production support and performance optimization.

Excellent communication skills.

Good-to-Have Skills

Private Equity / Investment Management domain experience.

Alteryx Designer Advanced or Expert Certification.

Python (Pandas), Snowflake and REST APIs.

Microsoft Entra ID and SCIM 2.0.

Git, CI/CD and workflow automation.

Key Responsibilities

Design, develop and maintain enterprise-grade Alteryx workflows.

Build reusable macros and optimize complex ETL/ELT processes.

Manage workflow deployment, scheduling and monitoring.

Perform performance tuning and troubleshoot production issues.

Integrate multiple databases, APIs and enterprise data sources.

Ensure data accuracy, reconciliation and operational reliability.

Coordinate with business and technical stakeholders.

Experience: 6+ years overall Data Engineering experience.

Must-have — candidates should have hands-on experience in ALL of these:

1. GCP (Google Cloud Platform) – strong hands-on experience
2. Python – data engineering/ETL development
3. SQL – advanced SQL, query optimization, data transformation
4. BigQuery – strong hands-on experience with development, optimization and data warehousing
5. Data Engineering / ETL – building and maintaining data pipelines
6. GCP data services – preferably Cloud Storage, Dataflow, Pub/Sub, Composer/Airflow, etc.
7. Data warehousing / dimensional modeling

DAT​​ABRICKS BI DEVELOPER / ENGINEER

Location: Remote

Experience: 5+ Years

Budget: Up to ₹25 LPA

Work Mode: Remote

Shift: US Eastern Time (ET) – Night Shift

Job Description

We are looking for an experienced Databricks BI Developer / Engineer with strong hands-on experience in Databricks and Apache Spark to support a dashboard migration project.

The primary responsibility will be migrating existing Tableau dashboards to Databricks AI/BI Dashboards.

Key Responsibilities

• Migrate existing Tableau dashboards to Databricks AI/BI Dashboards.
• Work with Databricks and Spark to analyse and process data.
• Understand business requirements and translate them into effective BI solutions.
• Collaborate with Databricks consultants, stakeholders, and technical teams.
• Handle ambiguous requirements and provide analytical solutions.
• Ensure dashboard accuracy, performance, and reliability.
• Communicate project progress and technical updates effectively.

Required Skills

• 5+ years of relevant professional experience.
• Strong hands-on experience with Databricks.
• Good experience with Apache Spark / PySpark.
• Experience with Tableau or other BI tools such as Power BI.
• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management skills.
• Ability to understand and work with evolving or ambiguous requirements.
• Willingness to learn Databricks AI/BI Dashboards quickly, if not already experienced.

Work Requirements

• Remote opportunity.
• Must be comfortable working in the US Eastern Time (ET) night shift.
• Budget: Up to ₹25 LPA.

Job Summary

We are seeking a skilled and detail-oriented Power BI Developer to design, develop, and maintain enterprise-level BI solutions. The ideal candidate should have strong expertise in Power BI, DAX, SQL, Data Modeling, and performance optimization tools such as DAX Studio, Tabular Editor, and ALM Toolkit. The candidate will collaborate with business stakeholders to transform data into actionable insights and deliver high-quality dashboards and reports.

Key Responsibilities

• Design, develop, and maintain interactive Power BI dashboards and reports.
• Create complex DAX measures, calculated columns, and calculated tables to meet business requirements.
• Develop and optimize SQL queries, stored procedures, views, and ETL processes.
• Design and implement scalable Star Schema and Snowflake Data Models.
• Perform report and model performance tuning using DAX Studio.
• Utilize Tabular Editor for model management, calculation groups, best practice analysis, and metadata enhancements.
• Manage model deployment, comparison, and version control using ALM Toolkit.
• Configure and manage Power BI Workspaces, Apps, Gateways, and Security (RLS/OLS).
• Work extensively with Power BI Service/Web Experience, including dataset refresh schedules, deployment pipelines, subscriptions, and workspace administration.
• Collaborate with business users to gather and analyze reporting requirements.
• Ensure data accuracy, governance, security, and report performance.
• Troubleshoot data-related issues and implement effective solutions.
• Create technical documentation and provide knowledge transfer to support teams.

Required Skills

Technical Skills

• Strong experience in Microsoft Power BI Development.
• Expertise in DAX (Data Analysis Expressions).
• Advanced knowledge of SQL Server/T-SQL and query optimization.
• Strong understanding of Data Modeling concepts (Star Schema, Snowflake Schema, Fact & Dimension Tables).
• Hands-on experience with Tabular Editor.
• Experience using DAX Studio for model and query performance tuning.
• Experience with ALM Toolkit for model comparison and deployment.
• Strong understanding of Power BI Service/Web Experience.
• Knowledge of Power Query (M Language).
• Experience with Row-Level Security (RLS) and data governance.
• Understanding of data warehousing and ETL concepts.

About Solutionara

Solutionara is an AI-led IT Consulting and Technology Services organization delivering enterprise transformation through Cloud, Integration, Data Engineering, Digital Experience, AI, and Enterprise Applications.

Headquartered in the United States with a Global Delivery Center (GDC) in Noida, India, Solutionara partners with enterprise organizations across retail, manufacturing, distribution, consumer goods, and other industries to design, implement, and support scalable technology solutions.

As a rapidly growing consulting organization, we foster a culture of ownership, innovation, collaboration, and continuous improvement, empowering our teams to contribute beyond their immediate responsibilities while delivering exceptional value to our global clients.

Every team member is expected to think like a consultant and business problem solver—understanding client objectives, challenging assumptions when appropriate, leveraging AI responsibly, and continuously identifying opportunities to improve quality, productivity, and customer outcomes.

AI is embedded into how we work, but it is an enabler—not a replacement for expertise, critical thinking, or accountability.

Role Overview

Solutionara is seeking a Senior Data Engineer with strong data engineering and database expertise to design, build, optimize, and support enterprise-scale data solutions.

This is a hands-on engineering position requiring strong SQL, Python, ETL/ELT, database, cloud, and troubleshooting capabilities. The engineer will work closely with technical leads and client stakeholders while taking ownership of major engineering components.

Location: Noida, India – Onsite | Employment Type: Full-Time | Experience: 6–9 Years

Key Responsibilities

Data Engineering

• Design, develop, test, deploy, and support scalable ETL/ELT pipelines.
• Build ingestion and transformation solutions across databases, APIs, files, and enterprise applications.
• Develop high-quality SQL and Python-based data processing solutions.
• Implement batch and incremental data-processing patterns.
• Develop reusable engineering components and frameworks.
• Support complex data migration and transformation activities.
• Perform source-to-target mapping and technical data analysis.
• Implement pipeline logging, monitoring, exception handling, and recovery mechanisms.

Database & Platform Engineering

• Design and optimize relational database schemas and data structures.
• Analyze and improve SQL/query performance.
• Support indexing, partitioning, storage optimization, and database performance.
• Implement appropriate database security and access controls.
• Support database monitoring, availability, backup/recovery, and operational requirements in collaboration with infrastructure/platform teams.
• Troubleshoot database and pipeline performance issues.
• Contribute to cloud data-platform configuration and optimization.

Data Quality

• Implement automated validation and data-quality controls.
• Develop reconciliation processes between source and target systems.
• Identify duplicate, incomplete, inconsistent, and invalid data.
• Implement cleansing, standardization, validation, and exception-management logic.
• Work with technical and business stakeholders to understand and implement business data rules.

Technical Delivery

• Convert technical designs into reliable production solutions.
• Participate in technical design and code reviews.
• Mentor junior/mid-level engineers.
• Support estimation and technical planning.
• Troubleshoot complex production and integration issues.
• Collaborate with technical leads, application teams, DevOps, QA, BI, and client teams.
• Document technical designs, mappings, configurations, operational procedures, and engineering decisions.

Consulting & AI-Led Working

• Understand the business purpose behind assigned engineering requirements.
• Raise risks, assumptions, dependencies, and potential improvements proactively.
• Communicate effectively with client and internal stakeholders.
• Use AI-assisted tools to improve coding, testing, analysis, documentation, and troubleshooting productivity.
• Independently verify AI-generated code and recommendations before implementation.
• Identify opportunities for engineering automation and process improvement.

Required Qualifications

• 6–9 years of experience in data engineering, database engineering, data integration, or related areas.
• Advanced SQL skills.
• Strong hands-on Python experience.
• Strong ETL/ELT development experience.
• Strong relational database knowledge, such as SQL Server, PostgreSQL, Oracle, or equivalent.
• Experience with data modeling and database design.
• Experience with AWS, Azure, or another major cloud platform.
• Experience with modern data technologies such as Databricks, Snowflake, Redshift, Synapse, Glue, ADF, Airflow, dbt, or equivalent.
• Experience with performance tuning and optimization.
• Experience with data validation and reconciliation.
• Strong troubleshooting and analytical skills.
• Ability to take ownership of engineering deliverables with limited supervision.

Preferred Qualifications

• Experience working with enterprise ERP, CRM, PIM, PLM, MES, or related systems.
• Experience with manufacturing, retail, distribution, or consumer-goods data.
• Experience with CI/CD and infrastructure/platform engineering practices.
• Experience with API and event-driven integrations.
• Previous consulting or technology-services experience.

What Success Looks Like

• Pipelines and databases perform reliably at enterprise scale.
• Engineering solutions are maintainable, reusable, and well documented.
• Data issues are detected and addressed systematically.
• Junior engineers receive effective technical guidance.
• Problems are owned through resolution rather than simply escalated.
• Engineering decisions reflect both technical requirements and client business objectives.